{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize the experiment results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '/media/hbai/data/code/LITE/results/scenarios/hotas'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[4], line 13\u001b[0m\n\u001b[1;32m     10\u001b[0m combined_results \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m     12\u001b[0m \u001b[38;5;66;03m# Loop through each subfolder\u001b[39;00m\n\u001b[0;32m---> 13\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m folder \u001b[38;5;129;01min\u001b[39;00m \u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlistdir\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m     14\u001b[0m     match \u001b[38;5;241m=\u001b[39m re\u001b[38;5;241m.\u001b[39mmatch(pattern, folder)\n\u001b[1;32m     15\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m match:\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/media/hbai/data/code/LITE/results/scenarios/hotas'"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import re\n",
    "import pandas as pd\n",
    "\n",
    "# Path to the MOT20-train directory\n",
    "path = \"/media/hbai/data/code/LITE/results/scenarios/hotas\" # path you evaluated the MOT results\n",
    "pattern = r\"^(.*?)__input_(\\d+)__conf_(\\d*\\.\\d+)$\"\n",
    "\n",
    "# Initialize a list to store results\n",
    "combined_results = []\n",
    "\n",
    "# Loop through each subfolder\n",
    "for folder in os.listdir(path):\n",
    "    match = re.match(pattern, folder)\n",
    "    if match:\n",
    "        TrackerName, input_res, conf_threshold = match.groups()\n",
    "        \n",
    "        # Path to the result file\n",
    "        result_file = os.path.join(path, folder, \"pedestrian_summary.txt\")\n",
    "        \n",
    "        if os.path.isfile(result_file):\n",
    "            with open(result_file, \"r\") as f:\n",
    "                # Read columns and values\n",
    "                columns = f.readline().strip().split()\n",
    "                values = f.readline().strip().split()\n",
    "                \n",
    "                # Add tracker settings to the results data\n",
    "                result_data = {\n",
    "                    \"TrackerName\": TrackerName,\n",
    "                    \"InputResolution\": int(input_res),\n",
    "                    \"ConfidenceThreshold\": float(conf_threshold)\n",
    "                }\n",
    "                result_data.update(dict(zip(columns, map(float, values))))\n",
    "                \n",
    "                combined_results.append(result_data)\n",
    "\n",
    "# Convert combined results into a DataFrame\n",
    "combined_df = pd.DataFrame(combined_results)\n",
    "combined_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import itertools\n",
    "# Assuming 'comparison_df' is defined and has the necessary data\n",
    "\n",
    "# List of distinct trackers\n",
    "trackers = ['DeepSORT', 'LITEDeepSORT', 'SORT', 'StrongSORT']\n",
    "# More markers can be added if needed\n",
    "markers = itertools.cycle(('o', 's', 'D', '^', 'v', '<', '>', 'P', '*'))\n",
    "line_styles = itertools.cycle(('-', '--', '-.', ':'))\n",
    "\n",
    "# Assigning a color to each tracker\n",
    "color_map = {tracker: plt.cm.tab10(i) for i, tracker in enumerate(trackers)}\n",
    "\n",
    "resolutions = sorted(combined_df['InputResolution'].unique())\n",
    "\n",
    "# Set consistent style for all plots\n",
    "plt.rcParams['lines.linewidth'] = 6  # Thicker lines\n",
    "plt.rcParams['legend.fontsize'] = 20  # Larger legend font size\n",
    "\n",
    "for res in resolutions:\n",
    "    df = combined_df[combined_df['InputResolution'] == res]\n",
    "\n",
    "    # Smaller figure size\n",
    "    plt.figure(figsize=(9, 5))  # Adjust the size to fit your page better\n",
    "\n",
    "    for tracker in trackers:\n",
    "        subset = df[df['TrackerName'] == tracker]\n",
    "        # Sort by confidence for plotting\n",
    "        subset = subset.sort_values(by='ConfidenceThreshold')\n",
    "        plt.plot(subset['ConfidenceThreshold'], subset['HOTA'],\n",
    "                 marker=next(markers), linestyle=next(line_styles),\n",
    "                 label=tracker, color=color_map[tracker])\n",
    "\n",
    "     # Set font size for x and y labels\n",
    "    plt.xlabel('Confidence Threshold', fontsize=20)\n",
    "    plt.ylabel('HOTA Score', fontsize=20)\n",
    "    plt.title(f'Input Resolution {res}x{res}', fontsize=22)\n",
    "\n",
    "    # Set font size for x and y ticks\n",
    "    plt.xticks(fontsize=16)\n",
    "    plt.yticks(fontsize=16)\n",
    "\n",
    "    # Set the x and y axis limits\n",
    "    plt.xlim(0, 0.8)\n",
    "    plt.ylim(2, 32)\n",
    "\n",
    "    # Place the legend on the bottom left\n",
    "    if res < 1280:\n",
    "            plt.legend(loc='upper right')\n",
    "    else:\n",
    "            plt.legend(loc='lower left')\n",
    "\n",
    "    plt.grid(True)\n",
    "    plt.tight_layout()\n",
    "    # Save the plots to the specified directory with a DPI suitable for high-quality printing\n",
    "    plt.savefig(f'MOT20-plots/effect_of_det_settings_on_HOTA_{res}x{res}_MOT20.png', dpi=300)\n",
    "    plt.show()\n",
    "    #plt.close()  # Close the plot to avoid displaying it inline if using a notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot HOTA and FPS of trackers in MOT17 and MOT20 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Data for both MOT17 and MOT20\n",
    "data = {\n",
    "    \"Tracker\": [\n",
    "        \"SORT\", \"OCSORT\", \"DeepSORT\", \"LITE:DeepSORT\" , \"DeepOCSORT\",\n",
    "        \"LITE:DeepOCSORT\", \"BoTSORT\", \"LITE:BoTSORT\", \"StrongSORT\", \"ByteTrack\"\n",
    "    ],\n",
    "    \"MOT17_HOTA\": [40.3, 43.9, 43.7,  43.0,  43.7,  43.7, 40.9, 40.8, 41.7, 43.8],\n",
    "    \"MOT17_FPS\": [32.0, 28.8, 13.7,  28.3,  10.6,  27.9, 19.1, 30.7, 5.1, 29.7],\n",
    "    \"MOT20_HOTA\": [20.1, 25.2, 24.8,  25.2,  24.9,  25.3, 20.8, 21.1, 24.8, 25.2],\n",
    "    \"MOT20_FPS\": [27.0, 24.2, 5.5,  23.4,  7.2,  22.7, 14.3, 24.2, 2.7, 24.4]\n",
    "}\n",
    "\n",
    "# Define color and shape mappings with exact naming match\n",
    "color_map = {\n",
    "    \"SORT\": \"blue\", \"DeepSORT\": \"green\", \"LITE:DeepSORT\": \"green\",\n",
    "    \"OCSORT\": \"gray\", \"DeepOCSORT\": \"yellow\", \"LITE:DeepOCSORT\": \"yellow\",\n",
    "    \"BoTSORT\": \"orange\", \"LITE:BoTSORT\": \"orange\",\n",
    "    \"StrongSORT\": \"purple\", \"ByteTrack\": \"red\"\n",
    "}\n",
    "\n",
    "shape_map = {\n",
    "    \"SORT\": \"o\", \"DeepSORT\": \"o\", \"LITE:DeepSORT\": \"s\",\n",
    "    \"OCSORT\": \"o\", \"DeepOCSORT\": \"o\", \"LITE:DeepOCSORT\": \"s\",\n",
    "    \"BoTSORT\": \"o\", \"LITE:BoTSORT\": \"s\",\n",
    "    \"StrongSORT\": \"o\", \"ByteTrack\": \"o\"\n",
    "}\n",
    "\n",
    "# Create DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# Plotting for MOT17 and MOT20\n",
    "fig, axes = plt.subplots(1, 2, figsize=(18, 8), sharey=True)\n",
    "\n",
    "# Function to plot data with border and line connection\n",
    "def plot_data(ax, dataset, title):\n",
    "    # Plot each tracker with specified color, shape, and black border\n",
    "    for i, row in df.iterrows():\n",
    "        sns.scatterplot(\n",
    "            x=[row[f\"{dataset}_HOTA\"]],\n",
    "            y=[row[f\"{dataset}_FPS\"]],\n",
    "            color=color_map[row[\"Tracker\"]],\n",
    "            marker=shape_map[row[\"Tracker\"]],\n",
    "            s=800,\n",
    "            edgecolor=\"black\",  # Black border around points\n",
    "            linewidth=1.5,\n",
    "            label=row[\"Tracker\"] if row[\"Tracker\"] not in ax.get_legend_handles_labels()[1] else \"\",\n",
    "            ax=ax\n",
    "        )\n",
    "\n",
    "    # Draw lines between each LITE tracker and its counterpart\n",
    "    pairs = [(\"DeepSORT\", \"LITE:DeepSORT\"), (\"DeepOCSORT\", \"LITE:DeepOCSORT\"), (\"BoTSORT\", \"LITE:BoTSORT\")]\n",
    "    for pair in pairs:\n",
    "        tracker1, tracker2 = pair\n",
    "        row1 = df[df[\"Tracker\"] == tracker1]\n",
    "        row2 = df[df[\"Tracker\"] == tracker2]\n",
    "        ax.plot([row1[f\"{dataset}_HOTA\"].values[0], row2[f\"{dataset}_HOTA\"].values[0]],\n",
    "                [row1[f\"{dataset}_FPS\"].values[0], row2[f\"{dataset}_FPS\"].values[0]],\n",
    "                color='black', linestyle=\"--\", linewidth=1.5)\n",
    "\n",
    "    # Customize plot\n",
    "    ax.set_title(f\"{title} Tracker Performance\", weight='bold', fontsize=26)\n",
    "    ax.set_xlabel(\"HOTA\", fontsize=25, fontweight='bold')\n",
    "    ax.set_ylabel(\"FPS\", fontsize=25, fontweight='bold')\n",
    "    ax.tick_params(axis='both', which='major', labelsize=25)\n",
    "    if dataset == \"MOT17\":\n",
    "        ax.set_xticks(range(40, 45, 1))\n",
    "    ax.get_legend().remove()\n",
    "\n",
    "# Plot MOT17\n",
    "plot_data(axes[0], \"MOT17\", \"MOT17\")\n",
    "\n",
    "# Plot MOT20\n",
    "plot_data(axes[1], \"MOT20\", \"MOT20\")\n",
    "\n",
    "# Adjust layout and set legend at the bottom\n",
    "handles, labels = axes[0].get_legend_handles_labels()\n",
    "fig.legend(handles, labels, loc='lower center', ncol=5, columnspacing=1.5, labelspacing=1.5, borderpad=1.5, frameon=True, fontsize=23, edgecolor=\"black\", framealpha=1, fancybox=False, shadow=False)\n",
    "\n",
    "plt.tight_layout(rect=[0, 0.28, 1, 1])  # Space at the bottom for legend\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize conf vs HOTA results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "imgsz = 1280\n",
    "\n",
    "# Define the directory path\n",
    "base_dir = f'../results/MOT17-train_{imgsz}_evaluated'\n",
    "\n",
    "# List of trackers with their line styles and colors\n",
    "tracker_styles = {\n",
    "    \"DeepOCSORT\": {\"line_style\": '--', \"color\": 'violet'},   # Purple\n",
    "    \"LITEDeepOCSORT\": {\"line_style\": '--', \"color\": 'b'},  # Orange\n",
    "    \"BoTSORT\": {\"line_style\": '-.', \"color\": 'brown'},          # Red\n",
    "    \"LITEBoTSORT\": {\"line_style\": '-.', \"color\": 'r'},   # Brown\n",
    "    \"LITEDeepSORT\": {\"line_style\": '--', \"color\": 'orange'},   # Gray\n",
    "    \"SORT\": {\"line_style\": ':', \"color\": 'gray'},               # Blue\n",
    "    \"OCSORT\": {\"line_style\": ':', \"color\": 'cyan'},        # Cyan\n",
    "    \"Bytetrack\": {\"line_style\": ':', \"color\": 'g'},        # Green\n",
    "    # \"StrongSORT\": {\"line_style\": ':', \"color\": 'magenta'}, # Magenta\n",
    "}\n",
    "\n",
    "# Dictionary to store confidence values and HOTA scores for each tracker\n",
    "tracker_data = {key: {\"conf\": [], \"hota\": []} for key in tracker_styles.keys()}\n",
    "\n",
    "# Loop through each folder in the base directory\n",
    "for folder in os.listdir(base_dir):\n",
    "    folder_path = os.path.join(base_dir, folder)\n",
    "    \n",
    "    # Skip if not a directory\n",
    "    if not os.path.isdir(folder_path):\n",
    "        continue\n",
    "    \n",
    "    # Check if the folder matches any of the tracker names\n",
    "    for tracker in tracker_styles.keys():\n",
    "        if re.match(rf'^{tracker}__input_{imgsz}__conf_\\d+\\.\\d+$', folder):\n",
    "            # Extract confidence value from the folder name\n",
    "            match = re.search(r'conf_(\\d+\\.\\d+)', folder)\n",
    "            if match:\n",
    "                conf = float(match.group(1))\n",
    "                \n",
    "                # Path to pedestrian_summary.txt\n",
    "                summary_file = os.path.join(folder_path, 'pedestrian_summary.txt')\n",
    "                \n",
    "                # Check if the file exists\n",
    "                if os.path.isfile(summary_file):\n",
    "                    # Read the file and get the HOTA value\n",
    "                    with open(summary_file, 'r') as f:\n",
    "                        f.readline()  # Skip the header line\n",
    "                        line = f.readline().strip()  # Read the values line\n",
    "                        \n",
    "                        # Split the line by spaces and take the first value as HOTA\n",
    "                        try:\n",
    "                            hota = float(line.split()[0])\n",
    "                            # Append confidence and HOTA to the tracker's lists\n",
    "                            tracker_data[tracker][\"conf\"].append(conf)\n",
    "                            tracker_data[tracker][\"hota\"].append(hota)\n",
    "                        except ValueError as e:\n",
    "                            print(f\"Error reading HOTA in {summary_file}: {e}\")\n",
    "            break  # Stop checking other trackers if a match is found\n",
    "\n",
    "# Plot HOTA vs. Confidence for all trackers in one plot\n",
    "plt.figure(figsize=(12, 8))\n",
    "\n",
    "# Plot each tracker with its specified line style and color\n",
    "for tracker, data in tracker_data.items():\n",
    "    if data[\"conf\"] and data[\"hota\"]:  # Check if there's data to plot\n",
    "        # Sort data by confidence values\n",
    "        sorted_data = sorted(zip(data[\"conf\"], data[\"hota\"]))\n",
    "        conf_values, hota_values = zip(*sorted_data)\n",
    "\n",
    "        # Get line style and color from the tracker styles\n",
    "        line_style = tracker_styles[tracker][\"line_style\"]\n",
    "        color = tracker_styles[tracker][\"color\"]\n",
    "        if 'LITE' in tracker:\n",
    "            marker = 'D'\n",
    "        else:\n",
    "            marker = 'o'\n",
    "        plt.plot(conf_values, hota_values, marker=marker, linestyle=line_style, color=color, label=tracker, linewidth=8)\n",
    "\n",
    "# Add labels, title, legend, and grid\n",
    "plt.xlabel('Confidence Threshold', fontsize=25, weight='bold')\n",
    "plt.ylabel('HOTA Score', fontsize=25, weight='bold')\n",
    "plt.xticks(fontsize=25)  # Adjust x-axis font size\n",
    "plt.yticks(fontsize=25)  # Adjust y-axis font size\n",
    "plt.title(f'Input Resolution {imgsz}x{imgsz} on Jetson Orin NX', fontsize=26)\n",
    "plt.legend(fontsize=20, ncol=2)\n",
    "# save the plot\n",
    "plt.savefig(f'hota_vs_conf_input_{imgsz}_MOT17.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize conf vs FPS results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "imgsz = 640\n",
    "\n",
    "# Load the CSV file\n",
    "file_path = f\"../results/MOT17-FPS_{imgsz}/MOT17-02-FRCNN/fps.csv\"\n",
    "data = pd.read_csv(file_path)\n",
    "\n",
    "# Define styles for each tracker\n",
    "tracker_styles = {\n",
    "    \"DeepOCSORT\": {\"line_style\": '--', \"color\": 'violet'},  \n",
    "    \"LITEDeepOCSORT\": {\"line_style\": '--', \"color\": 'b'},  \n",
    "    \"BoTSORT\": {\"line_style\": '-.', \"color\": 'brown'},       \n",
    "    \"LITEBoTSORT\": {\"line_style\": '-.', \"color\": 'r'},       \n",
    "    \"LITEDeepSORT\": {\"line_style\": '-', \"color\": 'orange'}, \n",
    "    \"SORT\": {\"line_style\": ':', \"color\": 'gray'},             \n",
    "    \"OCSORT\": {\"line_style\": ':', \"color\": 'cyan'},           \n",
    "    \"Bytetrack\": {\"line_style\": ':', \"color\": 'g'},           \n",
    "}\n",
    "\n",
    "# Plotting\n",
    "plt.figure(figsize=(12, 8))\n",
    "\n",
    "# Plot each tracker using the specified line style and color, in the order of tracker_styles\n",
    "for tracker, style in tracker_styles.items():\n",
    "    tracker_data = data[data['tracker_name'] == tracker]\n",
    "    sorted_data = tracker_data.sort_values(by='conf')\n",
    "    \n",
    "    line_style = style[\"line_style\"]\n",
    "    color = style[\"color\"]\n",
    "    marker = 'D' if 'LITE' in tracker else 'o'\n",
    "\n",
    "    # Plot confidence vs FPS\n",
    "    plt.plot(\n",
    "        sorted_data['conf'], \n",
    "        sorted_data['FPS'], \n",
    "        marker=marker, \n",
    "        linestyle=line_style, \n",
    "        color=color, \n",
    "        label=tracker, \n",
    "        linewidth=2.5\n",
    "    )\n",
    "\n",
    "# Add labels, title, and legend in specified order\n",
    "plt.xlabel('Confidence Threshold', fontsize=25, weight='bold')\n",
    "plt.ylabel('Frames Per Second', fontsize=25, weight='bold')\n",
    "plt.title(f'Input Resolution {imgsz}x{imgsz} on Jetson Orin NX', fontsize=26)\n",
    "plt.xticks(fontsize=25)\n",
    "plt.yticks(fontsize=25)\n",
    "plt.legend(fontsize=20, ncol=2)\n",
    "# save the plot\n",
    "plt.savefig(f'fps_vs_conf_input_{imgsz}_MOT17.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot HOTA and FPS of trackers in MOT17 and MOT20 Jetson Orin results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import re\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "imgsz_values = [640, 1280]\n",
    "\n",
    "# Define tracker styles\n",
    "tracker_styles = {\n",
    "    \"DeepOCSORT\": {\"line_style\": '--', \"color\": 'violet'},  \n",
    "    \"LITEDeepOCSORT\": {\"line_style\": '--', \"color\": 'b'},  \n",
    "    \"BoTSORT\": {\"line_style\": '-.', \"color\": 'brown'},       \n",
    "    \"LITEBoTSORT\": {\"line_style\": '-.', \"color\": 'r'},       \n",
    "    \"LITEDeepSORT\": {\"line_style\": '-', \"color\": 'orange'}, \n",
    "    \"SORT\": {\"line_style\": ':', \"color\": 'gray'},             \n",
    "    \"OCSORT\": {\"line_style\": ':', \"color\": 'cyan'},           \n",
    "    \"Bytetrack\": {\"line_style\": ':', \"color\": 'g'},           \n",
    "}\n",
    "\n",
    "# Create a figure with four subplots (2 rows, 2 columns)\n",
    "fig, axes = plt.subplots(2, 2, figsize=(24, 16), sharey='row')\n",
    "# fig.subplots_adjust(hspace=0.3) \n",
    "\n",
    "# Loop through each imgsz and plot both HOTA vs Confidence and FPS vs Confidence\n",
    "for i, imgsz in enumerate(imgsz_values):\n",
    "    # HOTA vs Confidence (Row 1)\n",
    "    base_dir = f'../results/MOT17-train_{imgsz}_evaluated'\n",
    "    tracker_data = {key: {\"conf\": [], \"hota\": []} for key in tracker_styles.keys()}\n",
    "\n",
    "    for folder in os.listdir(base_dir):\n",
    "        folder_path = os.path.join(base_dir, folder) \n",
    "        if not os.path.isdir(folder_path):\n",
    "            continue\n",
    "        \n",
    "        for tracker in tracker_styles.keys():\n",
    "            if re.match(rf'^{tracker}__input_{imgsz}__conf_\\d+\\.\\d+$', folder):\n",
    "                match = re.search(r'conf_(\\d+\\.\\d+)', folder)\n",
    "                if match:\n",
    "                    conf = float(match.group(1))\n",
    "                    summary_file = os.path.join(folder_path, 'pedestrian_summary.txt')\n",
    "                    if os.path.isfile(summary_file):\n",
    "                        with open(summary_file, 'r') as f:\n",
    "                            f.readline()  \n",
    "                            line = f.readline().strip()  \n",
    "                            try:\n",
    "                                hota = float(line.split()[0])\n",
    "                                tracker_data[tracker][\"conf\"].append(conf)\n",
    "                                tracker_data[tracker][\"hota\"].append(hota)\n",
    "                            except ValueError as e:\n",
    "                                print(f\"Error reading HOTA in {summary_file}: {e}\")\n",
    "                break  \n",
    "\n",
    "    ax_hota = axes[0, i]\n",
    "    for tracker, data in tracker_data.items():\n",
    "        if data[\"conf\"] and data[\"hota\"]:\n",
    "            sorted_data = sorted(zip(data[\"conf\"], data[\"hota\"]))\n",
    "            conf_values, hota_values = zip(*sorted_data)\n",
    "            style = tracker_styles[tracker]\n",
    "            marker = 'D' if 'LITE' in tracker else 'o'\n",
    "            ax_hota.plot(conf_values, hota_values, marker=marker, \n",
    "                         linestyle=style[\"line_style\"], color=style[\"color\"], \n",
    "                         label=tracker, linewidth=8)\n",
    "    ax_hota.set_title(f'HOTA vs Confidence Resolution {imgsz}x{imgsz}', fontsize=24)\n",
    "    ax_hota.set_xlabel('Confidence Threshold', fontsize=24)\n",
    "    ax_hota.tick_params(axis='both', labelsize=22)\n",
    "    ax_hota.grid(True)  # Add grid\n",
    "    if i == 0:\n",
    "        ax_hota.set_ylabel('HOTA Score', fontsize=24)\n",
    "\n",
    "    # FPS vs Confidence (Row 2)\n",
    "    fps_file = f\"../results/MOT17-FPS_{imgsz}/MOT17-02-FRCNN/fps.csv\"\n",
    "    data = pd.read_csv(fps_file)\n",
    "\n",
    "    ax_fps = axes[1, i]\n",
    "    for tracker, style in tracker_styles.items():\n",
    "        tracker_data = data[data['tracker_name'] == tracker]\n",
    "        sorted_data = tracker_data.sort_values(by='conf')\n",
    "        marker = 'D' if 'LITE' in tracker else 'o'\n",
    "        ax_fps.plot(\n",
    "            sorted_data['conf'], sorted_data['FPS'], \n",
    "            marker=marker, linestyle=style[\"line_style\"], \n",
    "            color=style[\"color\"], label=tracker, linewidth=8\n",
    "        )\n",
    "    ax_fps.set_title(f'FPS vs Confidence Resolution {imgsz}x{imgsz}', fontsize=24)\n",
    "    ax_fps.set_xlabel('Confidence Threshold', fontsize=24)\n",
    "    ax_fps.tick_params(axis='both', labelsize=22)\n",
    "    ax_fps.grid(True)  # Add grid\n",
    "    if i == 0:\n",
    "        ax_fps.set_ylabel('Frames Per Second', fontsize=24)\n",
    "\n",
    "# Add a single legend for all plots, at the bottom\n",
    "handles, labels = axes[0, 0].get_legend_handles_labels()\n",
    "fig.legend(handles, labels, loc='lower center', fontsize=26, ncol=4)\n",
    "\n",
    "# Adjust layout to make room for the legend\n",
    "# plt.tight_layout(rect=[0, 0.08, 1, 1])\n",
    "# Adjust spacing between rows and columns\n",
    "fig.subplots_adjust(hspace=0.3, wspace=0.05, bottom=0.15)  # Increased hspace for rows, set bottom margin for legend\n",
    "\n",
    "plt.savefig('hota_fps_vs_conf_MOT17_side_by_side.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get HOTA and other metrics to make results table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "# Directory where the trackers are stored\n",
    "base_dir = '/home/hbai/LITE/results/MOT17-train_1280_evaluated/'\n",
    "\n",
    "# Initialize a dictionary to store the results for each tracker\n",
    "metrics_summary = {}\n",
    "\n",
    "# Loop through each tracker folder in the base directory\n",
    "for tracker_folder in os.listdir(base_dir):\n",
    "    # Construct the path to pedestrian_summary.txt\n",
    "    if \"0.25\" not in tracker_folder:\n",
    "        continue\n",
    "    summary_file_path = os.path.join(base_dir, tracker_folder, 'pedestrian_summary.txt')\n",
    "    \n",
    "    # Check if the file exists\n",
    "    if os.path.isfile(summary_file_path):\n",
    "        with open(summary_file_path, 'r') as f:\n",
    "            # Read the data line by line\n",
    "            lines = f.readlines()\n",
    "            \n",
    "            # Header line for metrics (assuming it's the first line)\n",
    "            headers = lines[0].strip().split()\n",
    "            \n",
    "            # Values line (assuming it's the second line)\n",
    "            values = lines[1].strip().split()\n",
    "            \n",
    "            # Convert values to floats for easier manipulation if needed\n",
    "            values = list(map(float, values))\n",
    "            \n",
    "            # Create a dictionary for the metrics in this file\n",
    "            metrics = dict(zip(headers, values))\n",
    "            \n",
    "            # Extract the required metrics\n",
    "            metrics_summary[tracker_folder] = {\n",
    "                'HOTA': metrics['HOTA'],\n",
    "                'IDF1': metrics['IDF1'],\n",
    "                'MOTA': metrics['MOTA'],\n",
    "                'AssA': metrics['AssA'],\n",
    "                'DetA': metrics['DetA']\n",
    "            }\n",
    "\n",
    "# Print the extracted metrics\n",
    "for tracker, metrics in metrics_summary.items():\n",
    "    print(f\"{tracker.split('__')[0].rjust(20, ' ')}: & {metrics['HOTA']:.1f} & {metrics['IDF1']:.1f} & {metrics['MOTA']:.1f} & {metrics['AssA']:.1f} & {metrics['DetA']:.1f}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize GT detection and tracks of MOT17 and MOT20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import pandas as pd\n",
    "import os\n",
    "import random\n",
    "\n",
    "# Full Paths\n",
    "gt_path = '../datasets/MOT17/train/MOT17-02-FRCNN/gt/gt.txt' # path to the ground truth file\n",
    "\n",
    "img_folder = '../datasets/MOT17/train/MOT17-02-FRCNN/img1/' # path to the image folder\n",
    "\n",
    "# Load ground truth data\n",
    "gt_data = pd.read_csv(gt_path, header=None)\n",
    "gt_data.columns = ['frame', 'id', 'x', 'y', 'w', 'h', 'conf', 'class', 'visibility']\n",
    "\n",
    "# Sort by frame number and filter visible objects\n",
    "gt_data = gt_data.sort_values(by='frame')\n",
    "\n",
    "# Assign a random color to each object ID\n",
    "id_colors = {}\n",
    "unique_ids = gt_data['id'].unique()\n",
    "for obj_id in unique_ids:\n",
    "    id_colors[obj_id] = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))\n",
    "\n",
    "# Video writer\n",
    "first_frame = cv2.imread(os.path.join(img_folder, '000001.jpg'))\n",
    "height, width, _ = first_frame.shape\n",
    "out = cv2.VideoWriter('output.avi', cv2.VideoWriter_fourcc(*'XVID'), 30, (width, height))\n",
    "\n",
    "# Iterate over frames\n",
    "for frame_num in sorted(gt_data['frame'].unique()):\n",
    "\n",
    "\n",
    "    frame_path = os.path.join(img_folder, f'{frame_num:06d}.jpg')\n",
    "    frame = cv2.imread(frame_path)\n",
    "\n",
    "    if frame is None:\n",
    "        continue\n",
    "\n",
    "    # Get all boxes for the current frame\n",
    "    frame_data = gt_data[gt_data['frame'] == frame_num]\n",
    "\n",
    "    for _, row in frame_data.iterrows():\n",
    "        if row['class'] != 1:\n",
    "         continue\n",
    "\n",
    "        x, y, w, h = int(row['x']), int(row['y']), int(row['w']), int(row['h'])\n",
    "        obj_id = int(row['id'])\n",
    "        visibility = row['visibility']\n",
    "\n",
    "        # Get color for the current object ID\n",
    "        color = id_colors[obj_id]\n",
    "\n",
    "        # Draw bounding box\n",
    "        cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)\n",
    "\n",
    "        # Add text for ID and visibility level\n",
    "        text = f'ID: {obj_id}, Vis: {visibility:.2f}'\n",
    "        cv2.putText(frame, text, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)\n",
    "\n",
    "    out.write(frame)\n",
    "    cv2.imshow('Tracking', frame)\n",
    "\n",
    "    if cv2.waitKey(1) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "# Cleanup\n",
    "out.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tracker</th>\n",
       "      <th>resolution</th>\n",
       "      <th>conf</th>\n",
       "      <th>model</th>\n",
       "      <th>HOTA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.2</td>\n",
       "      <td>yolov8m</td>\n",
       "      <td>39.912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LITEDeepSORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.5</td>\n",
       "      <td>yolov8m</td>\n",
       "      <td>41.173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DeepSORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.2</td>\n",
       "      <td>yolo11m</td>\n",
       "      <td>40.210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bytetrack</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.3</td>\n",
       "      <td>yolo11m</td>\n",
       "      <td>43.642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.3</td>\n",
       "      <td>yolo11m</td>\n",
       "      <td>39.881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>StrongSORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.7</td>\n",
       "      <td>yolo11m</td>\n",
       "      <td>37.567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>SORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.4</td>\n",
       "      <td>yolo11m</td>\n",
       "      <td>38.377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>StrongSORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.2</td>\n",
       "      <td>yolov8m</td>\n",
       "      <td>43.621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>LITEDeepSORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.2</td>\n",
       "      <td>yolov8m</td>\n",
       "      <td>41.633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>SORT</td>\n",
       "      <td>1280</td>\n",
       "      <td>0.3</td>\n",
       "      <td>yolov8m</td>\n",
       "      <td>39.670</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>84 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         tracker resolution conf    model    HOTA\n",
       "0           SORT       1280  0.2  yolov8m  39.912\n",
       "1   LITEDeepSORT       1280  0.5  yolov8m  41.173\n",
       "2       DeepSORT       1280  0.2  yolo11m  40.210\n",
       "3      Bytetrack       1280  0.3  yolo11m  43.642\n",
       "4           SORT       1280  0.3  yolo11m  39.881\n",
       "..           ...        ...  ...      ...     ...\n",
       "79    StrongSORT       1280  0.7  yolo11m  37.567\n",
       "80          SORT       1280  0.4  yolo11m  38.377\n",
       "81    StrongSORT       1280  0.2  yolov8m  43.621\n",
       "82  LITEDeepSORT       1280  0.2  yolov8m  41.633\n",
       "83          SORT       1280  0.3  yolov8m  39.670\n",
       "\n",
       "[84 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "def parse_tracker_info(info_string):\n",
    "    components = info_string.split('__')\n",
    "    tracker_name = components[0]\n",
    "    resolution = components[1].split('_')[1]\n",
    "    confidence_input = components[2].split('_')[1]\n",
    "    yolo_model_type = components[3].split('_')[1]\n",
    "    # model, ablation, type = components[3].split('_')\n",
    "    # yolo_model_type = ablation + '_' + type\n",
    "\n",
    "    return {\n",
    "        \"tracker\": tracker_name,\n",
    "        \"resolution\": resolution,\n",
    "        \"conf\": confidence_input,\n",
    "        \"model\": yolo_model_type\n",
    "    }\n",
    "\n",
    "def extract_hota(summary_path):\n",
    "    # Read the pedestrian summary file and extract the HOTA value\n",
    "    try:\n",
    "        with open(summary_path, 'r') as f:\n",
    "            line = f.readline().strip()  # Read the first line\n",
    "            columns = line.split()  # Split by whitespace\n",
    "            hota_index = 0  # The first value corresponds to HOTA\n",
    "            hota_score = float(columns[hota_index])\n",
    "            return hota_score\n",
    "    except Exception as e:\n",
    "        print(f\"Error reading HOTA from {summary_path}: {e}\")\n",
    "        return None\n",
    "\n",
    "# Initialize an empty list to collect data\n",
    "data = []\n",
    "\n",
    "# Path to the directory containing result files\n",
    "path = '/home/hbvision/mirsaid/LITE/results/yolo/MOT17-train'\n",
    "\n",
    "files = os.listdir(path)\n",
    "\n",
    "for file in files:\n",
    "    # Parse the file name to get the tracker information\n",
    "    info = parse_tracker_info(file)\n",
    "    \n",
    "    # Path to the pedestrian summary file\n",
    "    summary_path = os.path.join(path, file, \"pedestrian_summary.txt\")\n",
    "    \n",
    "    # Check if the pedestrian summary file exists\n",
    "    if os.path.exists(summary_path):\n",
    "        results = pd.read_csv(summary_path, sep=' ')\n",
    "        hota_score = results['HOTA'][0]\n",
    "        \n",
    "        # Append the extracted data as a dictionary\n",
    "        data.append({\n",
    "            \"tracker\": info[\"tracker\"],\n",
    "            \"resolution\": info[\"resolution\"],\n",
    "            \"conf\": info[\"conf\"],\n",
    "            \"model\": info[\"model\"],\n",
    "            \"HOTA\": hota_score\n",
    "        })\n",
    "\n",
    "# Convert the list of dictionaries to a DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def matplotlib_setup(fontsize=45):\n",
    "    font = {'size'   : fontsize}\n",
    "    plt.rc('font', **font)\n",
    "    plt.rcParams[\"axes.linewidth\"]  = 2.5\n",
    "    plt.grid(linewidth=3,axis='y', color='grey')\n",
    "\n",
    "    CB91_Blue = '#2CBDFE'\n",
    "    CB91_Green = '#47DBCD'\n",
    "    CB91_Pink = '#F3A0F2'\n",
    "    CB91_Purple = '#9D2EC5'\n",
    "    CB91_Violet = '#661D98'\n",
    "    CB91_Amber = '#F5B14C'\n",
    "    color_list = [CB91_Blue, CB91_Pink, CB91_Green, CB91_Amber,\n",
    "              CB91_Purple, CB91_Violet]\n",
    "    \n",
    "    plt.rcParams['axes.prop_cycle'] = plt.cycler(color=color_list)    \n",
    "    return plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_54667/2900085205.py:59: UserWarning: Tight layout not applied. The left and right margins cannot be made large enough to accommodate all Axes decorations.\n",
      "  plt.tight_layout(rect=[1, 0.05, 1, 1])\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAqIAAAHiCAYAAAAzsa4CAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA4/0lEQVR4nO3de1xVdb7/8Q/XLSAiIl4wRXmEooV3wTJrMrw1OjNmmaXH1MlL59HFTmJy6nQ5OTaaJUc9zWOcU6mnJG00p2iO5d0aRRQVDU00r1B4AQIE5bp+f8zDfilrwd5rr72/e8Pr+Xjwh9/v3p/vZyGL9Wbvvdby0TRNEwAAAMDNfFU3AAAAgOaJIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJfzdtVBpaalkZWXJwYMHpaysrN5869atZc6cOe5qx2UyMzPliy++kMzMTPnuu++ksLBQKioqJDg4WCIiIiQuLk4SEhJkzJgxMmjQINXtAgAAKOPjinvNV1RUyOHDh2X//v1y4MAB2b9/v+Tm5kpDS0VHR8vZs2etbsVt1q9fL3/4wx/kyJEjdj+nT58+8tJLL8kjjzziws4AAAA8kyVB9Nq1a7J69eqfg2dOTo7U1tY6VMNbg+ilS5dk8uTJsmXLFtM1Ro4cKf/7v/8rkZGRFnYGAADg2SwJomfPnpVu3bo5VcMbg2hubq4kJSXJhQsXnK7VpUsX2bp1q8TGxlrQGQAAgOfjZCWTLly4IA888ECDIdTPz0969OghiYmJ0qtXLwkMDDR87Pnz52XYsGGWhFoAAABvQBA1obq6Wh555BHJy8vTnY+NjZXVq1dLSUmJfPfdd5KRkSE5OTlSWloqGzdulP79++s+Ly8vTx599FGprq52ZfsAAAAeweVB1NfXV3r16iVTpkyRZcuWSWpqqquXdLlFixbJvn37dOcmTZok2dnZMmXKFAkJCblpzmazybhx4yQzM1OSk5N1n793715ZvHix5T0DAAB4Gks/I+rj4yPdu3eXgQMHysCBA2XAgAHSv3//mwLZzp075f77769Xw1s+I5qXlyfdu3eXa9eu1ZsbP368rF+/Xnx97cv3zz//vG4wDw4OltzcXOnUqZOz7QIAAHgsS64jGhkZKTt27JABAwZIaGioFSU91ltvvaUbQqOiouT999+3O4TeqLVz5045fPjwTeMVFRWyZMkSWbp0qbPtAgAAeCxL3poPCQmRX/3qV00+hJaWlsp7772nO7dgwQJp1aqVQ/X8/f3l7bff1p37y1/+onvhfwAAgKaCk5UcsGHDBikvL6833rFjR5k8ebKpmsOGDdM9eam8vFw2btxoqiYAAIA3IIg6YN26dbrjjz/+uAQEBJiu+8QTTzi0HgAAQFNAELVTZWWl7N69W3du3LhxTtU2ev6uXbuksrLSqdoAAACeiiBqp7179+qepNSyZUtJTEx0qnbnzp2le/fu9cYrKiokIyPDqdoAAACeiiBqpwMHDuiO9+/fX/z9nb/4QEJCgu54VlaW07UBAAA8EUHUTocOHdId79OnjyX1+/Xrpzt+66WdAAAAmgqCqJ1OnjypO673lroZt99+u+54bm6uJfUBAAA8DUHUTmfOnNEd79q1qyX1jeoYrQsAAODtCKJ2qKyslCtXrujOdejQwZI1jOpcunRJqqqqLFkDAADAkxBE7VBYWGg417ZtW0vWaKhOUVGRJWsAAAB4EkvuNd/UFRcXG845eltPI76+vhISEqJ756bi4mKHXnk9f/68pKen//zvmJgYadmypSV9AgAA17h69aqcPn3653+PGTNGunTporAj1yOI2qGiosJwLjg42LJ1jIJoQ+vfUFlZ+fPF7z/55BOZO3euZX0BAAA1/vVf/1V1Cy5FELVDQ5/RtOIaoo3Vsuczom+++aa8/vrrlvUCAADganxG1A41NTWGc+4IotXV1Y0+NyUlRUpKSqSkpESWLFliWU8AAACuwiuidmgobNbW1oqfn58l6xgF3oCAgEafa7PZxGaziYjIHXfccdPcO++8I3feeafzDQIAAJf59ttv5d/+7d9+/ndMTIzCbtyDIGqHwMBAw7mamhqXB9GG1tdz64lJgwYNknvuucd0XwAAwPWCgoJu+ndzONGYt+bt0NAJSXonF5llVOvWH0wAAICmgCBqh/DwcMO50tJSS9aoq6szDKJt2rSxZA0AAABPQhC1Q0REhOFcQxe7d4TRnZtECKIAAKBpIojawWazGYbRgoICS9a4ePGi7nhkZKTDnxEFAADwBgRRO3Xr1k13/OzZs5bUN6rTHM6YAwAAzRNB1E6xsbG647m5uZbUP3nypEPrAgAAeDuCqJ369eunO56dnW1J/cOHD+uO9+3b15L6AAAAnoYgaqdBgwbpjh88eFBqa2udrp+Zmak7PmDAAKdrAwAAeCKCqJ0GDx4sLVq0qDdeVlZmGCLtlZeXJydOnKg3HhQUJHfddZdTtQEAADwVQdROLVq0kHvvvVd37tNPP3Wq9qZNm3TH77vvvp9v2wkAANDUEEQdMGHCBN3xtWvXGt6e0x5r1qxxaD0AAICmgCDqgIcfflj3dp/5+fny0Ucfmaq5c+dO2b9/f73x4OBgGT9+vKmaAAAA3qDJB9GpU6eKj49Pva+uXbs6XCssLEymT5+uO/fyyy9LWVmZQ/VqamrkhRde0J178sknpVWrVg73CAAA4C2afBC1WnJysu5JS3l5efL73/9eNE2zu9b8+fPl4MGD9caDgoJk7ty5TvUJAADg6QiiDurSpYukpKTozn3yyScydepUuX79eoM16urqJCUlRd5++23d+ZSUFOncubPTvQIAAHgyf6sKHTp0SJ555plGH1dSUqI7XlBQIPfcc49da33zzTcO9Wa1+fPnS3p6uu5nO9esWSMZGRnyyiuvyLhx4276TGlVVZX83//9nyxYsEAOHDigWzshIUFefPFFl/UOAADgKSwLoiUlJfKPf/zD9PMrKyuder47BQYGyieffCJ33323/PDDD/Xmc3NzZfLkyeLv7y+xsbESFhYmZWVlcurUKamsrDSsGxUVJevXr5fAwEBXtg8AAOARLAuizU10dLRs27ZNkpKSJD8/X/cxNTU1cvz4cbvq3XbbbbJ161aJjo62sk0AAACPxWdEnRAXFydZWVnywAMPOFUnKSlJsrKypEePHhZ1BgAA4PkIok5q3769bN26VdLS0iQ+Pt6h58bHx0taWpps2bJF2rVr56IOAQAAPJNlb83/6le/cujSRe6yatUqWbVqlcvXmThxokycOFEyMjLkiy++kMzMTDlx4oQUFhZKRUWFBAcHS0REhPTo0UMSExPl17/+tSQmJrq8LwAAAE/FZ0QtNnjwYBk8eLDqNgAAADweb80DAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJf1cv8OOPP0p6erps375djh07Jnl5eVJWViZ+fn4SFhYmMTExEh8fLyNHjpRRo0ZJcHCwq1sCAACAB3DZK6InT56Uxx57TLp06SIzZ86Ujz/+WI4cOSJFRUVSXV0t169fl4sXL8revXtl5cqVMn78eOnUqZPMnz9fSktLXdWWU6ZOnSo+Pj4u+5o7d67qTQQAAHAblwTRxYsXS3x8vHz88cdSU1Nj9/N++uknWbRokfTo0UO++uorV7QGAAAAD2FpEK2trZVJkybJiy++KJWVlabrFBQUyOjRo+Xdd9+1sDsAAAB4Eks/Izp9+nRZu3Ztg4/p2LGjdOrUSWpra+X8+fNSWFio+7i6ujp5+umnJSgoSKZNm2ZlmwAAAPAAlgXR5cuXy5o1a3TnWrRoIc8++6zMmjVLYmJibpo7cuSIrFixQt5//32pra29aU7TNHnqqaekd+/eMmDAAKtatdyQIUMsqdOtWzdL6gAAAHgDS4Lo999/L8nJybpz0dHR8vnnn0t8fLzufO/evWXlypUyadIkGTdunBQXF980X1lZKVOmTJHs7Gzx93f5Sf6mfPPNN6pbAAAA8DqWfEb0+eef1/1MaEREhOzYscMwhP7SfffdJ5s3bxabzVZv7tixY7JixQorWgUAAICHcDqIHjp0SD7//HPduT//+c8Ovd2ckJAgCxYs0J1btGiRUydAAQAAwLM4HUSXLl2qO37vvffK+PHjHa733HPP1fscqcg/z6Rv7EQoAAAAeA+ngujVq1dlw4YNunPz5s0zVTMgIEDmzJmjO2d0MhQAAAC8j1NBND09XSoqKuqNt2/fXkaNGmW67uOPPy4BAQH1xnft2iUFBQWm6wIAAMBzOBVEje5+NHbsWPHz8zNdNyIiQoYOHVpvXNM02bJli+m6AAAA8BxOBdHt27frjiclJTlTtsEaRmsCAADAu5gOoleuXJFz587pziUkJJhuqLEaWVlZTtcGAACAeqaD6KFDh3THW7VqZckdgvr166c7fvz4cS7jBAAA0ASYvlXRyZMndcdjY2NNN/NLbdq0kfDw8Hp3WqqpqZEzZ85IXFycJetYoaysTDIyMmTPnj1y4cIFuXz5spSUlIjNZpOwsDC57bbbJC4uTgYOHCh9+/YVX19L7iMAAADg1UwH0TNnzuiOd+3a1WxJ3Vq3BtEba3tSEA0PD5fa2lq7HhsZGSnjxo2T2bNnG77qCwAA0ByYDqJ5eXm64x06dDDdjL21jNZWxd4QKiJy+fJlWblypaxcuVJ++9vfyjvvvKN7AX8rXbt2TcrLy126BgAAcM61a9dUt+B2poNoYWGh7njbtm1NN3OryMhIh9b2Nn/7299k69atsmLFCpk6darL1klLS5M9e/a4rD4AAHCe0UngTZnpDyvqvWUu8s+TlawSGhrq0NreqLy8XKZNmyavvPKKU3UqKyultLRUSktLefUTAAB4BdOviOrdUUlEJDg42HQztwoJCXFobXfr2bOnDB8+XPr06SPx8fESFRUlYWFhYrPZpLi4WAoLCyU7O1t2794tmzZtkh9//NGw1htvvCGhoaGSnJxsqpc333xTXn/9dbObAgAA4HamXxGtqqrSHff3N51t7a5ltLY7xMTEyKJFi+TMmTNy7Ngx+a//+i+ZPn26DBo0SDp16iQtW7aUgIAAadeunfTs2VMmTpwo7777rpw9e1bee+896dixo2Ht+fPny44dO0z1lZKSIiUlJVJSUiKbN282u3kAAABuYzo11tTU6Bd0QxCtrq62bA1HvPbaaxIdHS0+Pj4OPzcwMFCmT58uY8aMkcmTJ+veqrSurk5mzpwp3377rdhsNofq22y2n59z6yvJjz32mNx9990O9wwAANxnz5498sEHH6huw61Mp0ajkOjIGeSNMQq7AQEBlq3hCCsuTdWuXTtJT0+XESNGyK5du+rNnzp1SlatWiWzZs1yeq0bgoKCDD/mAAAAPENQUJDqFtzO9FvzgYGBuuNG4dEMo1pGa3uLwMBA+fTTTw3fpl+2bJmbOwIAAHA/00HU6KQkK8/YNqrVFP5iCA8PNzxT/tixY5KTk+PmjgAAANzLdBANDw/XHS8tLTXdzK3Kysp0x9u0aWPZGio9+eSTht9HsyctAQAAeAvTQTQiIkJ33MqLzV++fNmhtb2Nv7+/JCUl6c5lZWW5uRsAAAD3Mh1EO3XqpDteUFBguplbXbx40aG1vdGQIUN0x8+cOePmTgAAANzLdBDt1q2b7vjZs2fNlrS7lqvvze5O7du31x2/cuWKmzsBAABwL9NBNDY2Vnf85MmTppv5paKiIikqKqo37u/vbxiCvZHR512vX7/u5k4AAADcy3QQ7devn+54SUmJJa+KHj58WHc8Li7O4Yu9ezKjE7K8/RJVAAAAjTEdRCMjIyU6Olp3LjMz03RDjdUYMGCA07U9idEJWWFhYW7uBAAAwL1MB1ERkfvvv193fNu2bc6UbbDGsGHDnK7tSQ4ePKg7bsVdnAAAADyZU0F0xIgRuuOfffaZ1NXVma5bVFQku3fvrjfu4+Mjw4cPN13XE3355Ze643feeaebOwEAAHAvp4LomDFjdO9yVFBQYBiw7JGWliZVVVX1xocOHWp4W0xvtHnzZjl//rzu3D333OPmbgAAANzLqSAaGhoqDz30kO7c4sWLTdWsqamR1NRU3bkpU6aYqumJ6urqJCUlRXcuMjKSIAoAAJo8p4KoiMjzzz+vO75z50759NNPHa63fPlyOXXqVL3x9u3by6RJkxyqNXXqVPHx8an35Qmfv5wzZ47hlQGmTZsmfn5+7m0IAADAzZwOogMGDJAHH3xQd27mzJkOXcrpwIEDhq8SJicnS4sWLcy06LQPPvhA0tPTLalVV1cnL730kixfvlx3PjQ01DDcAwAANCVOB1ERkdTUVN3rXl65ckWGDRsmOTk5jdb4+uuvZeTIkVJZWVlvLi4uTp599lkrWjUlOztbxo4dK3379pVVq1bJTz/9ZKrOiRMnZPjw4bJw4ULDxyxYsEA6dOhgslMAAADvYUkQjY2NlUWLFunOnTlzRgYNGiQpKSm690//9ttvZfbs2XL//ffr3kkpMDBQVq9eLQEBAVa06pTs7GyZNm2atGvXTkaPHi1Lly6VHTt2SHFxseFz8vPzJS0tTX73u99Jz549Zfv27YaPfeihh+SZZ55xResAAAAex9+qQnPmzJEDBw7IRx99VG/u2rVr8sc//lH++Mc/SqdOnSQqKkrq6urk3Llzjd5TfcWKFZKQkGBVm5aorq6WzZs3y+bNm38eCw8Pl9atW0tYWJjYbDYpLi6WoqIiu+8ZP3LkSPnoo4/Ex8fHVW0DAAB4FMuCqIjIqlWrpKamRtatW2f4mPz8fMnPz2+0lq+vr6SmpsqMGTOsbNFliouLG3xl1Iifn5+kpKTIq6++Kv7+lv53AAAAeDRL3pq/wd/fX9LS0mThwoVO3Su9Xbt2kp6e3uTfpu7Vq5fs2rVL3njjDUIoAABodiwNoiL/vPtRSkqKHD16VCZMmOBQwAoLC5Pk5GTJzc2V0aNHW92aaU899ZQsXLhQRowYIS1btnSqlq+vr/zmN7+RLVu2SE5OjgwZMsSiLgEAALyLj6ZpmisX+OGHH+Szzz6TnTt3Sk5OjuTn50tZWZn4+flJq1atJCYmRnr37i3Dhw+XBx98UEJCQlzZjtNqa2slNzdXDh8+LEePHpXTp0/LhQsXft6uiooKqa6ultDQ0J8/NxoVFSUJCQkyePBgSUxMlLCwMJf2+M0338jQoUN//vfXX3/NBfIBAPBwzfH47fL3g6OiomT27Nkye/ZsVy/lFn5+ftKzZ0/p2bOnPPbYY6rbAQAA8FqWvzUPAAAA2IMgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQgiAKAAAAJQiiAAAAUIIgCgAAACUIogAAAFCCIAoAAAAlCKIAAABQwt/VC/z444+Snp4u27dvl2PHjkleXp6UlZWJn5+fhIWFSUxMjMTHx8vIkSNl1KhREhwc7OqWXCYzM1O++OILyczMlO+++04KCwuloqJCgoODJSIiQuLi4iQhIUHGjBkjgwYNUt0uAACAUi4LoidPnpRXXnlF/vrXv0pNTU29+erqarl+/bpcvHhR9u7dKytXrpTWrVvLrFmz5N///d+lVatWrmrNcuvXr5c//OEPcuTIEd35srIyKSsrk7Nnz8rmzZvlP//zP6VPnz7y0ksvySOPPOLmbgEAADyDS96aX7x4scTHx8vHH3+sG0KN/PTTT7Jo0SLp0aOHfPXVV65ozVKXLl2SESNGyKOPPmoYQo1kZ2fLhAkTZNSoUXL58mUXdQgAAOC5LA2itbW1MmnSJHnxxRelsrLSdJ2CggIZPXq0vPvuuxZ2Z63c3FwZOHCgbNmyxak6X375pQwcOFBOnjxpUWcAAADewdK35qdPny5r165t8DEdO3aUTp06SW1trZw/f14KCwt1H1dXVydPP/20BAUFybRp06xs02kXLlyQBx54QPLy8gwf4+fnJ7fffru0bt1aysrK5NSpU1JVVaX72PPnz8uwYcNkz5490rlzZ1e1DQAA4FEse0V0+fLlsmbNGt25Fi1ayLx58+T777+XH374Qfbv3y8HDx6UK1euSHZ2tsyYMUP8/PzqPU/TNHnqqackKyvLqjadVl1dLY888ohhCI2NjZXVq1dLSUmJfPfdd5KRkSE5OTlSWloqGzdulP79++s+Ly8vTx599FGprq52ZfsAAAAew5Ig+v3330tycrLuXHR0tGRmZsqiRYskJiam3nzv3r1l5cqVsm3bNgkPD683X1lZKVOmTHHos6autGjRItm3b5/u3KRJkyQ7O1umTJkiISEhN83ZbDYZN26cZGZmGn6v9u7dK4sXL7a8ZwAAAE9kSRB9/vnndT8TGhERITt27JD4+PhGa9x3332yefNmsdls9eaOHTsmK1assKJVp+Tl5cnChQt158aPHy9r1qyRoKCgBmv4+fnJ4sWLZc6cObrzCxculPz8fGdbBQAA8HhOB9FDhw7J559/rjv35z//Wbp162Z3rYSEBFmwYIHu3KJFi5w6AcoKb731lly7dq3eeFRUlLz//vvi62v/t/Ott96Svn371huvqKiQJUuWONMmAACAV3A6iC5dulR3/N5775Xx48c7XO+5557TfQu/oKCg0ROhXKm0tFTee+893bkFCxY4fN1Tf39/efvtt3Xn/vKXv0hZWZnDPQIAAHgTp4Lo1atXZcOGDbpz8+bNM1UzICDA8G1ro5Oh3GHDhg1SXl5eb7xjx44yefJkUzWHDRume/JSeXm5bNy40VRNAAAAb+FUEE1PT5eKiop64+3bt5dRo0aZrvv4449LQEBAvfFdu3ZJQUGB6brOWLdune64Ua/2euKJJxxaDwAAoKlwKoga3f1o7NixupdjsldERIQMHTq03rimaU5fQN6MyspK2b17t+7cuHHjnKpt9Pxdu3Yp/0wsAACAKzkVRLdv3647npSU5EzZBmsYrelKe/fu1T1JqWXLlpKYmOhU7c6dO0v37t3rjVdUVEhGRoZTtQEAADyZ6SB65coVOXfunO5cQkKC6YYaq6Hi4vYHDhzQHe/fv7/4+zt/cypP2lYAAAB3MR1EDx06pDveqlUrhy7ZZKRfv36648ePH3f7W9ZG29qnTx9L6htt6+HDhy2pDwAA4IlMB9GTJ0/qjsfGxppu5pfatGmje6elmpoaOXPmjCVr2MtoW/XeUjfj9ttv1x3Pzc21pD4AAIAnMh1EjcJg165dzZa0u5a7g6irt9VTthMAAMCdTH/AMS8vT3e8Q4cOppuxt5bR2q5QWVkpV65c0Z2zaluN6ly6dEmqqqokMDDQqfrXrl3TvQYqAADwHHonRjd1poNoYWGh7njbtm1NN3OryMhIh9Z2hYbWsmpbG6pTVFTkcOC9evXqTf9OTU2VtLQ0U70BAAD3uHjx4k3/vvV43hSZDqLFxcW6447e6rIhoaGhDq3tCg2tZdW2+vr6SkhIiO6rlsXFxXYF0crKyp9P4srJyblp7u9//7slfQIAAPc5ffq06hZcznQQ1bujkohIcHCw6WZuFRIS4tDartDQWlZvq14QtXdb33zzTXn99dct6wcAAMDVTJ+sVFVVpTtuxXU1G6tltLYrNLSWJ21rSkqKlJSUSElJiSxZssSyvgAAAFzFdJKqqanRL+iGcFZdXW3ZGo0x2k4Rz9pWm80mNptNREQeeeQRERGZO3euLFmyRO644w5p2bKlNY0CUK68vFxGjRolmzdvNnznCID3uXr1quTk5Px8/B4zZozqllzOdJIyCk61tbWmm7mVUQgMCAiwbI3GNBQ2a2trxc/Pz5J1rNzWLl26yIwZM2Tu3LkyY8YMSz+3C0C90tJSERG566672L+BJubuu+9uVsdv02/NG11SqKFXEB1lVMvZyxk5oqG1mtq2AgAAuJPpIGp0oo6V16s0qhUUFGTZGo1p6IQkT95Wm80mr7766s9v1wNoOti/gaarue3fpt+a17v9psj/f8vICmVlZbrjbdq0sWyNxhhtp8g/t9WKXurq6gyDqNn6NptNXnvtNSe6AuCp2L+Bpqu57d+mXxGNiIjQHbfyYvOXL192aG1XaGgtq7bV6M5NIu4N3QAAAO5kOoh26tRJd7ygoMB0M7e69Q4Dja3tCjabzTCMWrWtRtsZGRnJZ0QBAECTZTqIduvWTXf87NmzZkvaXSsmJsayNezh6m31lO0EAABwJ9NBNDY2Vnf85MmTppv5paKiIikqKqo37u/vbxgMXcVoW3Nzcy2pb/Q9M1oXAACgKTAdRPv166c7XlJSYskrhYcPH9Ydj4uLc/uZZEbbmp2dbUl9o23t27evJfUBAAA8kemz5iMjIyU6OlrOnTtXby4zM1O6du3qTF+SmZmpOz5gwACn6poxaNAg3fGDBw/Wu6j9jz/+KOnp6bJ9+3Y5duyY5OXlSVlZmfj5+UlYWJjExMRIfHy8jBw5UkaNGiXBwcEeta2OyMzMlC+++EIyMzPlu+++k8LCQqmoqJDg4GCJiIiQuLg4SUhIkDFjxhh+DwFvYmb/BuA9SktLJSsrSw4ePKh75Z7WrVvLnDlz3N+YxTzq+K05YerUqZqI1PuaOXOmM2U1TdO0pKQk3dqrV692urajrl27prVo0UK3nz179miapmm5ubnaxIkTNX9/f93H6X21bt1ae+qpp3TngoKCtOvXr7t9W+2xbt06rXfv3nZvp4hoffr00davX6+6dcAUs/v3iy++qJWUlKhuX9cTTzzh0D7s6NcLL7ygehOBBpWXl2v/+Mc/tNTUVG3y5Mlajx49NB8fnwZ/rqOjo1W37RRPPH47FUTXrl2r23SHDh202tpa03ULCwu1wMDAenV9fHy0H374wZmWTRsxYoTutiYnJ2uLFi3SbDabpb/ER40apWQ7G3Lx4kVt+PDhTm3XyJEjtUuXLqneFMBuzu7fHTp00L788kvVm1EPQRTNTUVFhfanP/1Jmz59uta7d2/Nz8/P4Z9rbw2innz8diqIlpaWakFBQboN//3vfzddd8WKFbo17733Xmfadcr//M//6PZktP3Ofr3//vvKtlXPiRMntM6dO1uybV26dNFyc3NVbxLQoJqaGu3xxx+35Gfe19dX++///m/Vm3QTgiiamzNnzjj9c+2NQdTTj9+mT1YSEQkNDZWHHnpId27x4sWmatbU1Ehqaqru3JQpU0zVtMLDDz+s+3mva9euNfi8jh07ysCBA6Vfv352X4g/ODhYxo8fb6pPV7hw4YI88MADcuHCBcPH+Pn5SY8ePSQxMVF69erV4PVPz58/L8OGDWuwHqDa9OnTZe3atQ0+xt79u66uTp5++mn54IMPrG4TAAx5xfHb2SR74MABw+S8ceNGh+u98847urXat2+vXbt2zaFaRn/xm/2L5umnn7brL4YWLVpo8+bN077//vt6NbKzs7UZM2Zovr6+hs+fOHGiqf5coaqqSktMTDTsNTY2Vlu9erV29erVm553/fp1bePGjVr//v0Nn3vXXXdpVVVVirYMMLZs2TKn9m+jt/xsNpt24MABBVtUn9HvxyFDhljytWLFCtWbCNykub0i6i3Hb6eDqKZp2oMPPqjbaNu2bbUzZ87YXWf//v2Gn8VasmSJw31ZHUTPnTtneNLSL2sfOXKk0VoTJkxo8IejurraVI9We+ONNwz7nDRpklZRUdHg82tqarTk5GTDGgsWLHDTlgD2OXXqlOHvIXv37507d2rh4eG6NXr16uUR+7fR70egqWooiPr6+mq9evXSpkyZoi1btkxLTU31+iDqLcdvS37r5Obm6p5cJCJat27dtG+//bbRGrt379batGmjWyMuLs5U8rY6iGqapr3++uuG/yk2m007fvx4g8+vra3V5s+f3+hfXUuXLjXdo1UuXLhg+BnY8ePHO3RC2pw5c3TrBAcHa3l5eS7cCsAxY8eO1f1ZjYiI0E6fPm13nX379hkGWk/YvwmiaG5uBFEfHx+tR48e2qRJk7SlS5dqu3fvrveq4I4dO7w6iHrT8duy3zpLly41DFVBQUHa/PnzdX+JHz16VJs1a5bhW1mBgYHavn37TPXkiiC6b9++BgNk9+7dtQ8//FArLy+/6XmVlZXapk2btIEDBzYaQkX+eaat6ss3Pfvss7q9RUVFOXxJmurqaq1v37669ebMmeOiLQAcc/DgQcN98q9//avD9d566y2P3b8Jomhurl69qu3YsUMrLS1t9LHeHkS96fht6W+dSZMmNRqwOnXqpA0aNEgbMGCA1rZt20Yfv3LlStP9uCKI/su//ItdQdLf31/r2bOnNnjwYO2OO+4wdfkXlWfOl5SUaCEhIZb2tW3bNt16ISEhdv1iAFzNaP82e8WOqqoqLSYmxuP2b00jiAIN8eYg6m3Hb6fOmr/VqlWr5NFHH23wMfn5+bJ//37JysqSK1euGD7O19dXli1bJjNmzLCyRadcvXpVNmzYYNdja2pq5Pjx45KRkSE5OTlSWVlp+NjWrVvrjq9Zs8ZMm5bYsGGDlJeX1xvv2LGjTJ482VTNYcOGSf/+/euNl5eXy8aNG03VBKzS0P49b948UzUDAgIM78Kicv8G0HR52/Hb0iDq7+8vaWlpsnDhwgZP/29Mu3btJD09XZ555hkLu3Neenq6VFRUWFozKSlJ9u7dKwEBAfXmdu3aJQUFBZauZ69169bpjj/++OO6vdrriSeecGg9wF2M9u/27dvLqFGjTNc12mdU7t8Ami5vO35bGkRFRHx8fCQlJUWOHj0qEyZMEH9/+29nHxYWJsnJyZKbmyujR4+2ujWnffXVV7rj999/v8THxztUKz4+XtLS0mTLli0SFxcnQ4cOrfcYTdNky5Ytpnp1RmVlpezevVt3bty4cU7VNnr+rl27GnzVGHA1o/177Nix4ufnZ7puRESER+3fAJoubzx+Wx5Eb+jevbusW7dOzp07J3/605/k0UcflTvvvFPCw8PF399fbDabREZGSmJiosyYMUPWr18v+fn5snjxYgkLC7Okh1WrVon2z8/B3vR19uxZU/W2b9+uOz5r1iw5cuSI7N27V15++WUZMWKEREdHS8uWLcXX11datmwp0dHRMmLECPmP//gPycjIkCNHjsjEiRN/rpGUlOTQmq60d+9e3Qv1t2zZUhITE52q3blzZ+nevXu98YqKCsnIyHCqNuAMo33NaN90hCft3wCaLm88ftv/cqVJUVFRMnv2bJk9e7arl3KpK1euyLlz53TnEhISRERk8ODBMnjwYFP1b9S4VVZWlql6zjhw4IDueP/+/R16hdtIQkKC5Obm1hvPysqS++67z+n6gKPs2b+d4Un7N4CmyxuP3y57RbSpOXTokO54q1atpFu3bk7X79evn+748ePH3f6WtdG29unTx5L6Rtt6+PBhS+oDjmpO+zeApssbj98uf0W0qTh58qTueGxsrCX127RpI+Hh4VJcXHzTeE1NjZw5c0bi4uIsWcceRtuq95K8GbfffrvuuN5fWYA7NKf9uzFlZWWSkZEhe/bskQsXLsjly5elpKREbDabhIWFyW233SZxcXEycOBA6du3r/j68noG4Cm88fhNELXTmTNndMe7du1q2Rpdu3atd6C6sbY7D1Su3lajOkbrAq7WnPbvxoSHh0ttba1dj42MjJRx48bJ7NmzDV8pAeA+3nj85k9ZO+Xl5emOd+jQwbI1jGoZre0KlZWVhtd3tWpbjepcunRJqqqqLFkDcERz2b/tYW8IFRG5fPmyrFy5Uvr37y+/+93v5PTp0y7sDEBDvPX4TRC1U2Fhoe5427ZtLVsjMjLSobVdoaG1rNrWhuoUFRVZsgbgiOayf7vS3/72N+ndu7esWrVKdStAs+Stx2+CqJ303lIT+efJDFYJDQ11aG1XaGgtq7bV19dXQkJCHF4fcJXmsn+7Wnl5uUybNk1eeeUV1a0AzY63Hr/5jKidjO6oFBwcbNkaRv+5Vt/NqSENrWX1turdgsyd2wrc0Fz274b07NlThg8fLn369JH4+HiJioqSsLAwsdlsUlxcLIWFhZKdnS27d++WTZs2yY8//mhY64033pDQ0FBJTk524xYAzZu3Hr8JonYy+uyDFdflaqyWOz832dBaTW1bgRuay/59q5iYGJk1a5ZMmDChwZMZ2rVrJ+3atZOePXvKxIkTJTU1VT788EN5+eWXDQPp/PnzZeDAgXL//fe7qHsAv+Stx2/emrdTTU2N7rg7/nOrq6stW6MxRtsp0vS2Fbihuezfv/Taa6/JqVOnZN68eQ6fURsYGCjTp0+Xw4cPy/Dhw3UfU1dXJzNnzuQ6qYCbeOvxmyBqJ6NvvCNnmDbG6IcoICDAsjUa09APa1PbVuCG5rJ//1LXrl3Fx8fHqRrt2rWT9PR0wzuqnDp1ipOXADfx1uM3QdROgYGBuuMN/QXiKKNaRmu7QkNrNbVtBW5oLvu3KwQGBsqnn34qHTt21J1ftmyZmzsCmidvPX4TRO1k9EFfvQ/smmVUKygoyLI1GtPQB5qb2rYCNzSX/dtVwsPDDc+UP3bsmOTk5Li5I6D58dbjN0HUTuHh4brjpaWllq1RVlamO96mTRvL1miM0XaKWLetdXV1hj/I7txW4Ibmsn+70pNPPmn4fdyxY4ebuwGaH289fhNE7RQREaE7buXFqC9fvuzQ2q7Q0FpWbavRnR9Ems5BGd6luezfruTv7y9JSUm6c1lZWW7uBmh+vPX4TRC1U6dOnXTHCwoKLFvj4sWLDq3tCjabzfCH2aptNdrOyMhIr/+8HLxTc9m/XW3IkCG6487chxqAfbz1+E0QtVO3bt10x8+ePWvZGka1YmJiLFvDHq7eVk/ZTuCG5rR/u1L79u11xxt6FQWAdbzx+E0QtVNsbKzu+MmTJy2pX1RUpHufVn9/f8MfLFcx2tbc3FxL6ht9z4zWBVytOe3frmT01tz169fd3AnQPHnj8Zsgaqd+/frpjpeUlFjyl8bhw4d1x+Pi4sRmszld3xFG25qdnW1JfaNt7du3ryX1AUc1p/3blYxOyOIjN4B7eOPxmyBqp8jISImOjtady8zMdLq+UY0BAwY4XdtRgwYN0h0/ePCgJRfF9aRtBUSa1/7tSkYnZIWFhbm5E6B58sbjN0HUAUb3TN62bZvTtY1qDBs2zOnajho8eLC0aNGi3nhZWZnTB+W8vDw5ceJEvfGgoCC56667nKoNOKO57N+udPDgQd1xR28hCsAcbzx+E0QdMGLECN3xzz77TOrq6kzXLSoqkt27d9cb9/HxMbyPsyu1aNFC7r33Xt25Tz/91KnamzZt0h2/7777mtRblPA+zWX/dqUvv/xSd/zOO+90cydA8+SNx2+CqAPGjBmje+eAgoICw1/A9khLS5Oqqqp640OHDjW8bZ6rTZgwQXd87dq1Tt0qbM2aNQ6tB7hLc9q/XWHz5s1y/vx53bl77rnHzd0AzZe3Hb8Jog4IDQ2Vhx56SHdu8eLFpmrW1NRIamqq7tyUKVNM1bTCww8/rHu7sPz8fPnoo49M1dy5c6fs37+/3nhwcLCMHz/eVE3AKs1p/7ZaXV2dpKSk6M5FRkYSRAE38rbjN0HUQc8//7zu+M6dO0297L18+XI5depUvfH27dvLpEmTHKo1depU8fHxqfdl5vNZYWFhMn36dN25l19+2fDsWCM1NTXywgsv6M49+eST0qpVK4d7BKzWXPZvq82ZM8fwbNpp06aJn5+fexsCvExzPn4TRB00YMAAefDBB3XnZs6c6dClXg4cOGD4KkJycrLuB47dyaiHvLw8+f3vfy+aptlda/78+bonMgQFBcncuXOd6hOwSnPYvz/44ANJT0+3pFZdXZ289NJLsnz5ct350NBQw3APwHW86fhNEDUhNTVV97p4V65ckWHDhklOTk6jNb7++msZOXKkVFZW1puLi4uTZ5991pJendGlSxfDA+knn3wiU6dObfRC1Tfesnv77bd151NSUqRz585O9wpYpanv39nZ2TJ27Fjp27evrFq1Sn766SdTdU6cOCHDhw+XhQsXGj5mwYIF0qFDB5OdAjDLq47fGkxZunSpJiK6X0FBQdr8+fO106dP13ve0aNHtVmzZml+fn66zw0MDNT27dtnqqcnnnhCt2Z0dLTp7aysrNQGDRpkuK3du3fXPvzwQ628vLze8zZt2qQNHDjQ8LkJCQlaZWWl6d4AV2nK+/dzzz130/MDAgK0UaNGae+88462fft2raioyPC5eXl52tq1a7Xf/va3mo+Pj+H3SES0hx56SKurqzO1rYCrHDx4UBsyZEijX3feeafuz7XNZrPr+UOGDHGor+Z8/CaIOmHSpEkN/iIWEa1Tp07aoEGDtAEDBmht27Zt9PErV6403Y8rfpA1TdPOnj2rRUVFNdi3v7+/1rNnT23w4MHaHXfcodlstgYfHxUVpZ09e9apvgBXaqr7961BVO8rPDxc69atm9a3b18tMTFR6969u13bd+Nr5MiR2rVr10xvK+AqO3bssPvn2NkvRzTn47e/wLRVq1ZJTU2NrFu3zvAx+fn5kp+f32gtX19fSU1NlRkzZljZoiWio6Nl27ZtkpSUZLgtNTU1cvz4cbvq3XbbbbJ161bDO9kAnqC57N96iouLpbi42OHn+fn5SUpKirz66qvi78/hBVDNG47ffEbUCf7+/pKWliYLFy506l7K7dq1k/T0dHnmmWcs7M5acXFxkpWVJQ888IBTdZKSkiQrK0t69OhhUWeAazSn/dsKvXr1kl27dskbb7xBCAU8iKcfvwmiTvLx8ZGUlBQ5evSoTJgwwaFfwGFhYZKcnCy5ubkyevRoF3Zpjfbt28vWrVslLS1N4uPjHXpufHy8pKWlyZYtW6Rdu3Yu6hCwVlPcv5966ilZuHChjBgxQlq2bOlULV9fX/nNb34jW7ZskZycHBkyZIhFXQKwkicfv300zYFz+NGoH374QT777DPZuXOn5OTkSH5+vpSVlYmfn5+0atVKYmJipHfv3jJ8+HB58MEHJSQkRHXLpmVkZMgXX3whmZmZcuLECSksLJSKigoJDg6WiIgI6dGjhyQmJsqvf/1rSUxMVN0u4LSmtn/X1tZKbm6uHD58WI4ePSqnT5+WCxcu/LxdFRUVUl1dLaGhoRIeHi6tW7eWqKgoSUhIkMGDB0tiYqKEhYWp3gwADvKk4zdBFAAAAErw1jwAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABACYIoAAAAlCCIAgAAQAmCKAAAAJQgiAIAAEAJgigAAACUIIgCAABAif8H5ppJVJD1tf4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "matplotlib_setup()\n",
    "# Define specific styles for each tracker\n",
    "trackers = ['SORT', 'LITEDeepSORT', 'DeepSORT', 'Bytetrack', 'StrongSORT', 'OCSORT']\n",
    "colors = [plt.cm.tab10(i) for i in range(len(trackers))]\n",
    "markers = ['o', 's', 'D', '^', 'v', '<']\n",
    "line_styles = ['-', '--', '-.', ':', '-', '--']\n",
    "\n",
    "# Create a mapping for styles\n",
    "style_map = {tracker: {\"color\": colors[i], \"marker\": markers[i], \"linestyle\": line_styles[i]} for i, tracker in enumerate(trackers)}\n",
    "\n",
    "# Group data by model, tracker, and confidence\n",
    "curve_data_model_tracker = df.groupby([\"model\", \"tracker\", \"conf\"])[\"HOTA\"].mean().reset_index()\n",
    "\n",
    "# Set unique models\n",
    "models = curve_data_model_tracker[\"model\"].unique()\n",
    "n_models = len(models)\n",
    "\n",
    "# Create subplots\n",
    "fig, axes = plt.subplots(1, n_models, figsize=(25, 8), sharey=True)\n",
    "fig.suptitle(\"HOTA Scores for Different Trackers and Models\", fontsize=30)\n",
    "# adjust a bit space after the suptitle\n",
    "plt.subplots_adjust(top=0.85)\n",
    "axes = axes.flatten()  # Ensure axes is iterable\n",
    "\n",
    "plt.subplots_adjust(wspace=0.05)\n",
    "\n",
    "for ax, model in zip(axes, models):\n",
    "    model_data = curve_data_model_tracker[curve_data_model_tracker[\"model\"] == model]\n",
    "    for tracker in trackers:\n",
    "        tracker_data = model_data[model_data[\"tracker\"] == tracker]\n",
    "        if not tracker_data.empty:\n",
    "            ax.plot(\n",
    "                tracker_data[\"conf\"],\n",
    "                tracker_data[\"HOTA\"],\n",
    "                label=tracker,\n",
    "                color=style_map[tracker][\"color\"],\n",
    "                marker=style_map[tracker][\"marker\"],\n",
    "                linestyle=style_map[tracker][\"linestyle\"],\n",
    "                linewidth=6,\n",
    "                markersize=12\n",
    "            )\n",
    "    # Add subplot details\n",
    "    ax.set_title(f\"{model}\", fontsize=29)\n",
    "    ax.set_xlabel(\"Confidence Threshold\", fontsize=29)\n",
    "    ax.tick_params(axis='both', labelsize=30)\n",
    "    if ax == axes[0]:\n",
    "        ax.set_ylabel(\"HOTA Score\", fontsize=29)\n",
    "        # ax.legend(fontsize=20, title=\"Tracker\", title_fontsize=22, loc='lower left')\n",
    "\n",
    "# Create a single legend below the subplots\n",
    "handles, labels = axes[0].get_legend_handles_labels()\n",
    "fig.legend(handles, labels, title=\"Trackers\", title_fontsize=30, fontsize=30,\n",
    "            loc='lower center', ncol=3, bbox_to_anchor=(0.5, -0.3))\n",
    "\n",
    "# Adjust layout and save the plot\n",
    "plt.tight_layout(rect=[1, 0.05, 1, 1])\n",
    "plt.savefig(\"hota_scores_v8_11.png\", dpi=600, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABQUAAAN0CAYAAAANrk5eAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd1gUVxcG8HcLRao0sQIqWLD3LrYYY4u9Ro3dxJLk0xRNM830olETo0aNXWNLYoyx94oFe0HEhgpSpS678/0xQtgCbJllF3h/zzOP7OzMnbPCzs6eufcemSAIAoiIiIiIiIiIiKjUkNs6ACIiIiIiIiIiIipaTAoSERERERERERGVMkwKEhERERERERERlTJMChIREREREREREZUyTAoSERERERERERGVMkwKEhERERERERERlTJMChIREREREREREZUyTAoSERERERERERGVMkwKEhERERERERERlTJKWwdARPbl8ePHOHfuHKKiopCUlISsrCy4urqiQoUKqFGjBurXrw+lsvifOhITE3H27FlERkYiISEBmZmZKFOmDMqVK4eQkBA0atQITk5Otg7TYunp6Thz5gyuX7+OxMREpKWlwcPDA97e3qhfvz7q1KkDuZz3h6jkEQQBly9fxtWrV3Hv3j2kpqZCLpfD3d0dQUFBqFevHgICAmwdpiRu3ryJS5cu4c6dO3j69CkEQYC7uzsCAgIQGhqKkJAQW4dIRGSU0nIdWlwkJSUhPDwc0dHRSExMRGpqKsqUKQM3NzdUrFgRQUFBCAkJgbOzs61DJSJzCURkExqNRmjfvr0AIHepVKmSkJiYaFG7KpVKaNKkiVa7NWrUENLS0vLdJzY2Vvjss8+EunXrau1naHFzcxMGDhwo7Nixw6I4AwMDtdr98MMPLWrPGCkpKcLcuXOF5s2bC3K5vMDX6ezsLHTv3l1Yv369kJ2dbfXYpLZ9+3ahR48eglKpLPB1enh4CBMnThQuXbpk65CpmLp06ZLg5OSk9Xc1efJki9s9deqUoFAotNp97733Ct3v2LFjwpgxYwQfH59Cz2dVq1YV3n77beHWrVtmx7lv3z69dqOiosxuz1iXLl0Spk2bJlSsWLHQ11mhQgVhypQpQkREhGTHT05OFvbt2yd89dVXwoABA/TO6VKf17OysoTTp08LP/30kzB69Gihbt26eufxsLAwyY5HpsvIyBC8vb31/g4WL15s69BKvWXLlun9Xiyl296yZcvMbsva16GGXr81l8I+A+z9vZKSkiIsXLhQaNy4sSCTyQp9vUqlUmjYsKEwceJEYfPmzUJSUpKtXwIRmYBJQSIbunHjhuDi4qL1wTpmzBiL2pwzZ45We3K5XDh8+LDBbTMzM4XZs2cLrq6uZl30NG3aVDh16pRZcRZlUlCtVgvz5883KklgaKlRo4bw77//Wi0+KT18+FDo2bOnya9RqVQK77//frFMgJLtffbZZ1p/TzKZTNi/f7/Z7WVlZQn16tXTarNevXpCZmZmvvvcvHlT6Natm1nvcaVSKbz66qtmfZEp6qTgw4cPhWHDhhn1RU13kclkwuDBg4WYmBizjr1jxw7h5ZdfFkJDQwu9sSLFef3y5cvC1KlThRYtWuglng0tTAra1oYNGwz+Xtq0aWPr0Eo9e00KFtV1qL0lBe35vfLXX38ZdbOpoKVixYq2fhlEZAImBYls7Pvvv9f7MN25c6dZbV25ckXvi9Prr79ucNvo6GihUaNGBX6oOzg4CJ6engVuo1AohG+++cbkWIsqKfjkyROhS5cuhb6GsmXLFvol+4033rDrpNnDhw+FmjVr5hu/s7Oz4O3tXWDvwREjRghqtdrWL4WKGUM9lKtXry6kpqaa1d4HH3yg1ZZSqRROnz6d7/br1q3Tu8Giu7i7uwvOzs4FbhMYGCicO3fOpFiLMim4d+9ewdfXt8DX4OLiUugXbG9vb2H37t0mH3/UqFEmfTG09Lxu6hd5JgVtq3v37vn+bm7cuGHr8Eo1e0wKFuV1qL0lBe31vWLoO4nu78Pb27vQzxh/f3+bvQYiMh0nZCCysWnTpmHTpk04fPhw7rrx48fj4sWLcHd3N7odjUaDMWPGIDMzM3ddcHAw5syZo7ftjRs30KFDBzx48EBrvZOTE/r164fBgwejVatW8PPzg0wmQ0ZGBqKiovDHH39g1apVuHjxYu4+arUaM2bMwIMHD/Dtt9+a8tKtLjY2Fh07dsSlS5e01svlcvTs2RODBw9Ghw4d4O/vD4VCgaysLNy7dw9///03Vq9ejePHj2vt9/333+P+/ftYs2YNFApFUb4Uo4wYMQLXrl3TWlepUiW8/fbb6N27NwIDAwGIfysRERFYuXIl5s+fj6ysrNztV65ciYYNG+J///tfkcZOxZtSqcTy5cvRpEmT3L+nyMhIvPvuu/j+++9NaisiIgKff/651rq33noLTZo0Mbj9ggULMGXKFL31AQEBeOmll9C/f3/UqFEDbm5uAID4+HicP38e69evx7p165CUlJS7T3R0NNq2bYudO3eidevWJsVtbVu3bsWgQYOgUqm01vv5+WHYsGEYOHAg6tSpg7JlywIQ54G6cuUKNm7ciNWrV+PRo0e5+8THx6Nbt25Yv349+vXrV5Qvg0qohw8fYufOnfk+v3z5cnz66adFGBHZs6K+Dm3VqhV++ukno+N79913ER8fn/u4R48e6Nmzp9H7+/j45Pucvb5XNmzYgDfeeENvfe/evTF8+HC0bNlSax7erKws3LhxA6dOncL+/fuxbds2JCYmFmHERCQZW2cliUgQrl+/LpQpU0brLtvEiRNNauO7777T2l8mkwkHDx7U2y42NlYICgrSu6vXqlUr4fLly4UeR61WC999953BXjlffPGF0fFau6dgenq60LRpU70YQ0NDhaNHjxrVxsqVKw0OOZ40aZKksUrh77//1ouzWbNmwpMnTwrc79SpU3p34d3d3YWEhISiCZxKlE8++UTrb0kulwtHjhwxen+VSiU0btxYq406derkO2x4w4YNej18FQqF8OabbxY4j2qOBw8eCH379tV773h6egrXrl0zKuai6Cl45MgRwdHRUe84L7/8shAfH1/o/omJicL48eP1/q8cHByEQ4cOGR2Hbk/BatWqCYMHDxa+/fZb4eDBg0LlypUlPa/r9u7x8/MTunfvLnz44YfCX3/9pfe7Y09B2/nqq6/03od5HwcEBLAXug3ZU09Be7kOLYg1r1Ht8b2SkpIiVKhQQSsOHx8fk6YBycrKEv7880+ha9euQoUKFawYLRFJjUlBIjvx7bff6iX19uzZY9S+N2/e1Ls4mjZtmsFtDc251adPH0GlUpkU75EjR/SGDygUCqO/YFo7KThx4kS919myZUshJSXFpHauXbsm+Pv767W1Zs0aSeO11IgRI7Tic3JyEqKjo43ad9WqVXqvb9WqVVaOmEoiQ0m9mjVrCunp6Ubtrzs3oUKhyHe+qJs3bxo8B61fv97kuN944w2990DdunULnMMwh7WTgvHx8Xpf1gCYNW3DDz/8oNdO+fLlC715kOOnn34SPvnkE+Gff/4xuI/U5/W9e/cKb775prBx40bh9u3bes/rJimZFLSdOnXqaP0uZs6cqTdcf9euXbYOs9Syp6SgvVyHFsSa16j2+F5ZtGiR1vFNvaGny9D5mojsF5OCRHZCrVYLrVu31vpQrlq1qvD06dMC99NoNEJYWJjWfvnN5WUo+RMWFmbUF19D/v33X72eJ7Vq1TLqws6aF1yHDh0yGJe5vd8iIiL0kq5+fn5G9dApKtWrV9eKb+DAgUbvq1arBT8/P639J0yYYMVoqSQ7f/684ODgoPX39Oabbxa63+XLl/XmRH3nnXfy3d7QXKE///yz2XHrJtYBCJ988kmh+1k7KThu3Di99gv6fynMe++9p9fe2LFjJYm1qKvKMyloH06ePKmXULh//74waNAgrfXDhw+3daillr0kBe3pOrQg1jqX2et7pUePHlrH79GjR5Een4hsSw4isgtyuRy//vornJ2dc9dFRUXhnXfeKXC/n376CQcOHMh9LJPJ8Ouvv8LFxUVru+zsbLz//vta65ydnbF06VI4OjqaFfNzzz2H8ePHa627evUqVqxYYVZ7Upk1axYEQch9LJPJsHjx4ty5tkxVr149vPfee1rrYmNj8d1331kSpqQePnyo9bh58+ZG7yuXy9GsWTOtdTExMZLERaVP/fr19d4v3333HU6ePJnvPobmRA0NDcXs2bMNbr9nzx7s3r1ba12XLl0wceJEs+OeN28eypUrp7Xu66+/RkJCgtltWur69etYtmyZ1rrQ0FB8/PHHZrf5wQcfoE6dOlrrli9fjuvXr5vdJpVuy5cv13rcuXNnVKxYESNHjtRav2XLFiQnJxdhZGRPStN1aH7s9b2iO/d2WFhYkR2biGyPhUaI7EjNmjXxySef4M0338xdt2DBAgwcOBDt27fX2/7OnTt6ScPJkycb3HbLli2IiorSWjd9+nRUr17dopi/+OILrF+/Xmuy/u+//x5jx461qF1znTp1CocOHdJaN2zYMLRt29aidmfMmIGlS5ciMjIyd93ChQvx3nvvwcnJyaK2paBWq7Uee3p6mrS/bsJUt5iBOW7fvo0TJ07g7t27yMzMhI+PDxo3boxmzZpBJpMVuv+FCxdw5swZPHr0CDKZDOXLl0fr1q0t/pstDh4/fozz58/j1q1bSEpKQlZWFlxcXODp6YmgoCDUqFEDVapUsXWY+Zo1axa2bNmCc+fOARD/PkePHo0zZ84YfL/88MMPWoV9FAoFli1blu97SzchL5fLsWDBAotiLlu2LD7//HOtc1dycjKWLl2KGTNmWNS2uebOnav33p47dy4cHBzMbtPBwQHz5s1D586dc9ep1WrMmzcP8+fPN7vd0iArKwvHjh3D5cuXkZCQAEdHR1StWhXt27eHn59fofsnJSXh6NGjuHHjBlJSUuDl5YXq1aujQ4cOdvE5Yo7MzEysXbtWa92oUaMAAM8//zz8/f1zi9ykpaVhw4YNGDduXJHHaY4HDx7g6NGjiImJQUpKCsqWLYvatWujdevWxfb3ZUul5To0P/b8XslbiArQvyYsaklJSTh+/DgePnyIuLg4ZGZmwsPDAwEBAahTp47FfzNRUVE4c+YMHj9+jISEBHh6eqJcuXKoX78+atasKdGr0CYIAi5cuICIiAjExMQgMzMTXl5e6NGjB4KCggrdPyEhAceOHcOjR48QGxsLpVIJPz8/hISEoFmzZhYXQNRoNLh+/ToiIiLw6NEjpKSkQC6Xw8XFBf7+/qhatSpCQ0Nzi7ZRCWPrropEpE2tVgstW7bU6sYfHBxscNL8rl27Gj3cWHdogFwuF+7evStJzIbm78tvHrAc1hqaMXnyZL1YjC0sUpjPP/9cr+2NGzfqbac73G/UqFFmH/Ptt9/Waqtnz54GtwsJCdHaztTJtp9//nmt/ceMGVPg9h9++GG+v79du3bp/Q3nXapXry5s2LDBYLsajUZYvHixEBwcnO/+LVu2FE6ePGnS6zOFLX5/giC+9hUrVhT4f5d3qVChgjB06FBh27ZtZsdnTefOndMbRjxr1iy97W7cuKFXaOmtt97Kt92HDx/qTczetWtXSWJOT08XypYtq9V2nTp1CtzHWsOHs7Ky9GKpUaOGxe3mqFmzplbbZcuWFbKysixqs7gPH9b9PeZISkoSZsyYIXh4eBh8Lzo4OAijRo0SHj16ZLDdmzdvCsOGDdMbHp+zuLm5CR9++KHRc2/ak/Xr12u9Fnd3d63pS3Tn62zTpk2B7d25c0eQy+W528tkMuHWrVtmxZaQkKA3V9vp06cL3W/fvn1CmzZt9Ial5v19TZs2TWtezfz+duyFPQwftrfr0IJY41wm9XtFSrpT5Fj73G1IVlaW8PPPPwvNmzfX+4zXXSpXrixMmDBBOH78uNHtp6WlCV9++aXeZ5/uUrVqVeHDDz8UkpOTTYpf928m5zogPT1d+Pzzz/UKcRnzvsnOzhaWLVsmtGzZssD/E29vb2HSpEnCgwcPTIpZEMTCPzNmzDA4d7HuIpfLhfr16wszZ840uhgbFQ/296lFRAbn1nr99de1tlmyZInW8zKZTNi7d6/B9tLS0vQujJ9//nnJ4j1+/LjeB8fs2bML3MdaXx51K9rVrFlTknYFQRDu37+v9WUFEKt/6jpy5IjWNq6uriYXOBEE8WKgYsWKWm1t3rzZ4La6iazevXsbfRyVSqWXfFiyZEmB+xhKCmo0GmHGjBmFXlTkLLrzzCUmJhqcJ87QolQqDSZkpWCL319sbKzenKLGLp6enha+Yuv54IMP9H5veb+UazQaoX379lrb1KpVq8DkiKEvt2vXrpUs5kmTJum1X9Ck6dZKChpq9/PPP7e43RxffPGFXvumVJo0pCQmBS9evKj3uvJbKleuLFy9elWrzfXr1+sVQ8hvadu2rUnnGt3zsFR/e6Z44YUXtI4/evRorefPnTunF+ONGzcKbPO5556T5O9o4cKFWu3Ur1+/wO3VarXB939+S4UKFXITT4b+duyJrZOC9ngdWhBrnMus8V6RStWqVbWOW69ePUGj0RTJsQVBEP755x8hICDArGsgY4qa7N+/P9+kXH6Ln5+f8Oeffxr9GgwlBW/cuCHUqlWrwOPk9745deqUEBoaalLMLi4uwq+//mp0zH/99Zfg5eVl1v/7a6+9ZvRxyP5xTkEiO1S7dm189NFHWuvmzZuHo0ePAhCHtEyfPl3r+UmTJqFjx44G2zt58iQyMjK01nXp0kWyeJs3bw53d3etdQcPHpSsfWNFR0fj9u3bWuukfJ0VK1ZE7dq1tdYZep2tW7fWGn6QmpqKjRs3mny8nTt34sGDB7mPfX190bNnT4Pb6s6l9vfff+PatWtGHWfJkiVITEzMfezh4YGBAweaHO/bb7+Nb775Rmuds7NzvkOZv/76a/z8888AgPT0dHTt2lVvnjh3d3e4urrq7ZudnY2hQ4fi/PnzJsdZmKL+/WVmZqJTp065729dLi4u8PX1Nfj/YO/ee+891K9fP/dxdnY2Ro8enTs8feHChVrvIUNzq+rKO4dqDinf53mH1eawxfmstLxOexYVFYVOnTohOjo6d51MJoOXl5fBOdDu3buHHj16IDU1FQCwceNGDB06NPcxIA6N9/Lyglyufwl++PBhjBkzxgqvxDpiYmLw77//aq3TnRutQYMGWucAQH9eNV2jR4/WerxixQqteYKNpTsfp267eWk0GowcOTL3M0mXk5MTPDw8tNbFxMSga9euuHHjhsmxlTal5To0P9Z6r0ilRYsWWo8vXLiAGTNmQKPRWP3Y3333HXr06IE7d+4YfN7JyQne3t75Do8t7NywadMmPP/887h3757ecznnc0Pn49jYWPTp0wdLly414lXou3//Pjp27IirV69qrS9Tpoze36qurVu3IiwsDJcvXzYYs6enp8FrwrS0NIwZMwZffPFFofEdPHgQffv2NThvskwmg4eHB3x8fMye75OKGVtnJYnIsOzsbKF58+Zad2Vq1qwppKenC7169dJaHxQUVGDvgh9++EHvDk9+vQrNpdvbx9vbu8DtrXEXduvWrXqv05Q7ZsYYOXKkVvsymUxISkrS2063F067du1MPtaAAQO02tDtLarr1Vdf1dq+du3ahQ7N2bVrl97QzQULFhQam24Plbx/q5UqVRLmz5+vdeyEhARh8eLFelWOPT09hbi4OGHMmDFabf3+++9CYmJi7v7R0dHCrFmzBKVSqbV/69atC43VHEX5+5szZ47e323fvn2F7du3aw1PEwRxeM3FixeFVatWCcOHDxfKli1r1z0FBUEQzpw5o/d7++CDD4Tbt28Lbm5uWuunT59eaHsNGzbU2icgIEDSeG/duqX3+/jf//6X7/bW6inYp08frTYdHByEjIwMi9vNkZGRoTe8u1+/fha1WdJ6CuY9rw0ePFjYt29f7hBrjUYjnDlzRu99DkB49913hStXruT2EHRxcRHeeecdISIiIrf3TVZWlrBjxw6hQYMGevv/+++/RsVr656CX375pdaxAwMDDfYu+uabb/Tes2q1Ot92DQ3j37Nnj0mxXbx4Ue/98/jx43y3/+677/T+L318fIRvv/1WiI6Ozt3u6dOnwpYtW4S2bdvmbteiRQu9fe2NrXsK2uN1aEGkPpdZ670ild9//13v9wNAaNiwobB8+XIhISHBKsc19HeZcw20adMmvWug6OhoYdOmTcLo0aNze7gVdM6LiIgwOG3DsGHDhAMHDuRWqc7OzhZOnTolTJw4UW9EkEKhEA4dOlToa9H9m6lTp07uzw0aNBBWrVolxMbG5m6fnJws/P7778KxY8e02jly5IjeNZOXl5fwzjvvCCdOnNCa5iMuLk5Ys2aN3ueITCYT/v7773xj1Wg0ej0YPT09hffff184c+aM3rVGQkKCcOjQIeGrr74SwsLCBJlMxp6CJYz9fWoRUa5Lly7pfZjpzjcmk8mE3bt3F9jO1KlT9T4QdT9oLWXoGAVdRFjjy+O3336rF0N4eLjF7RZ2jLNnz+ptd//+fa35P2QymXDz5k2jj/PkyRO9331ERESB+6hUKmHw4MF6FxLvv/++cPLkSSEpKUlQqVTC48ePhZ07dwovvfSS3sVPYYnHHIa+jAIQOnbsaDBJmuPq1at683LlTXK//fbbBQ5ZWbVqlVH//5Yqyt+f7oXZN998Y/RxUlNThVWrVhm9va289957el/QmzRporWuRo0aRs2p5u7urvf3IzXdv9EXX3wx322tlRSsV6+eVpv16tWzuM3CjtGgQQOL2itpSUEAgpOTk/D7778XuN+ECRO09vH29hbatGkjAOKX/ytXruS7b0pKil6iu6C/t7xsnRTUHdr23nvvGdwuJiZGbz6sXbt2Fdj2K6+8orX9iBEjTIpNdyqLghLeUVFRenOqNWjQoMAkokajEWbNmmXwbwawv69Xtk4K2uN1aEGkPpdZ870iBY1GIzRq1Cjfv2elUik0b95cmDZtmrBq1Srh6tWrFg8vjoiI0BtS7uvrKxw4cMCo/VNTU4W5c+fmO5erSqXSSszlXHts2rSpwHb37Nmjdz4ICAjId872HPlNM/H6668bndh98uSJUKVKFa39O3fuLDx8+LDA/VQqlV7HgHLlymnNWZmX7nB7Ly8v4fr160bFKAjiPLmm3qgh+2Z/n1pEpMVQL6K8y8SJEwttQ7cng0KhkDzOjz76SC+2S5cu5bu9Nb48GprP7s6dOxa3m9eKFSv0jrF9+3aD23bv3t2oi0BDfvzxR619mzRpYvS+S5cu1buoKGypVKmSsHLlSqOPYejLaPXq1Y2aD+uTTz4xGMOwYcOMOnbHjh219nv33XeNjtsURfH7S0tL09quYsWKRdIroKhlZmbqJaDyLnK5XDhy5Eih7Tx9+lRv38KK4phDd36lZs2a5buttZKCvr6+Wm126tTJ4jZ16b6X/Pz8LGqvJCYFf/rpp0L3S05O1uvZBogJxcJu5giCIBw4cEDvi6uh4mK6bJkUPHHihN6xC/pSqTuf2vDhwwts/+TJk1rbu7i4GD3xv0qlEvz9/bX2L2huMN0CDz4+PoV+Cc8xfPhwg3839ia/HllSLgUlBe3xOrQgUp7LrP1ekUpkZKTeaI6CFi8vL+HFF18U5s6dK8TExJh8vN69e2u15+bmVuANFFPpFnYBCp8vO4ehkUfz588vcB9DScEBAwaYFPO7776rtX+rVq2MLkCl0Wj0/k9//PFHg9vqzrf6zjvvmBQnlTycU5DIzr311lto2rSpwecCAwPx9ddfF9pGSkqK1mPdeXGkYGjeuKdPn0p+nILovk7AcFyWMOV16s4NtWLFCqPnZzFlLiRDx927dy969OhR6LZKpRJvvfUWbty4gZdeesnoYxjy9ddfw83NrdDthg8frrfOyckJ33//vVHH0Y0zPDzcuABNVBS/P925XAIDAw3ObVPcOTo6YtmyZVAqlQaff+2119C6detC2ymK97ihNov6XAbov9aS+jrtWf369TFp0qRCt3N3d0fv3r311r/yyiuoV69eofu3b98eAQEBuY9VKhUiIiJMC7aI6c511qpVK4SEhOS7/ahRo7Qeb9myBcnJyflu36xZM9StWzf3cVpaGtavX29UbDt27MCjR49yH5cvXx7dunUzuG1mZiZWrFihte7jjz+Gv7+/Ucf67rvvUKZMGaO2Lc1Ky3WoIdZ+r0ilWrVqOH36NFq2bGnU9gkJCdi2bRtee+01VKlSBf369cOVK1eM2vfSpUv4888/tdZ99913qFWrlslx5+fHH3/UetyuXTuMHTvWqH1ffPFF9OnTR2vdvHnzTDq+g4ODSfs8ffoUCxcuzH2sUCiwZMmSAudYzksmk+Hbb7/Vmnvxl19+Mbit7rVn1apVjY6TSqaS982DqIRRKBRYvny5wYleFy9eXOhktQCQlZWl9dgaBQsMtZmZmSn5cQqi+zoB6V+rKa+zV69e8PHxyX189+5d7Nmzp9BjXLhwAWfOnMl97OTkhGHDhhkVX0xMDIYOHYqaNWti+/bthW6fnZ2Nr776CvXr18dvv/1m1DEM8fPzM/il2JCqVatq/b8A4v9VuXLljNq/WbNmWo+NvQg1VVH8/nS/xFy5ckWrKEFJ0qRJE7z11lt660NCQvDZZ58Z1UZRvMcNtVnU5zLANudtW7xOezZu3Dijt9U9L5m6v+7NP2POa7Nnz4YgjvrJXYKCgow+prkyMzOxbt06rXW6RRN0vfjii1rnu7S0NGzYsKHAfXRvpujebMmP7nYjR47M94bE6dOnER8fn/u4TJkyGDFihFHHAYBy5cqhb9++Rm9fWpWW61BDxy+K94pUAgICcPToUaxduxZNmjQxer/s7Gxs2bIF9erVyz0vFWTz5s1a21SqVMmkm9+FSUpK0iveNnXqVJPaeO2117QeX79+HZGRkUbv36tXL1SoUMHo7Xfu3KmVrOvcuTNCQ0ON3h8AgoODtT5LLl68qHV+y1G2bFmtx6dPnzbpOFTyGP6EJCK7UqdOHfTv3x9r167NXdeqVSs899xzRu2vm1C0RtLBUJtOTk6SH6cghhKnqampkt6RNuV1Ojo6Yvjw4Vp3CpcvX17o7033C02fPn3g5eVVaGwnTpxAjx498OTJE631QUFB6NKlC6pXrw5XV1ckJiYiIiICu3fvzq06fPPmTYwaNQqbN2/GunXrjL4zmaNNmzb5VoYzJCAgQCvOdu3ambRvXnkrJ0upKH5/rq6uqFOnDi5dugRAfC2DBw/Gr7/+anSStDj58MMPMWfOHK11M2bMMLqnTX7vcanptlnU5zJAfK15v9CW1Ndpz9q3b2/0trrnJW9vb5O+0BXVeU0KW7du1fry6uTkhMGDBxe4j7OzMwYOHIglS5bkrlu+fHmBidOXXnoJ77zzTm618qNHj+LGjRsF9rKKi4vDX3/9pbWuoGTD8ePHtR63adPGqJuteb3wwgtYs2aNSfvYg59++smi/V955RWjty0t16G6iuq9IiWZTIYhQ4ZgyJAhuHz5MrZt24Z9+/bh2LFjhfa8VKvV+Oijj3D79u0CKyfv379f6/HgwYPzTdyb4/jx41ojOxwcHNCrVy+T2ggLC4Ovry/i4uJy1x09ehTVq1c3av+OHTuadLwDBw5oPX7hhRdM2j9H48aNceLECQCAIAg4fvw4unfvrrVN8+bNtR7/+uuvaNiwISZNmlQiR6tQ4ZgUJComdC+oTCkRrzuk0xrDEJKSkgo9rrUZOl5SUpKkSUFTX+eYMWO0kkpbtmxBUlJSvkMBVSoVVq1apbXOmLunt27dQrdu3bS+SHp7e2PBggUYNGiQwQ/5p0+f4uuvv8Znn30GtVoNANi2bRsGDhyIP/74AzKZrNDj5ggMDDR6W0D/jr4p++v+fxsaUiqVovj9TZo0SesO9vbt2xEYGIi+ffuid+/e6Nixo9FD2eydofOWJecywPB70lK6bRb1uSznmHmTgiX1ddozU85Luue0gIAAk86hRXles5Tul/1evXoZdeNq1KhRWomOI0eO4ObNmwgODja4fbly5dCjRw9s3bo1d92yZcv0bizktXr16twkIgC0bNmywCGJV69e1XrcqFGjwl6GHnP2sQfGDI0viClJwdJyHaqrqN4r1hIaGorQ0FDMnDkTGo0G169fx9mzZ3H06FHs2bMn3x7NK1asQLNmzTB58mSDz+cdTQHAqOlDTKE7/ULdunVNvtktk8nQpEkT7Ny5M992C2LM1BF56d6guHHjBn7++WeT2gCAqKgorccxMTF62zRt2hRNmjTJnX5HrVZj8uTJ+PrrrzFkyBC88MILaNGihc2T6lR0mBQkKgV0u6+r1WokJCQYdWFiLN3eaQBQsWJFydo3hqFu+nFxcahSpYpkxzD1dTZo0ACNGjXC2bNnAQDp6elYt24dJk6caHD77du3IzY2Nvdx5cqVjeoROnHiRK2EoJeXF44cOVLglyE3Nzd89NFHqFWrltbw1r/++guLFy/GhAkTCj1uDlPnO9PtVWhK4lZ3X2Pn+TNHUfz+XnnlFezYsQN///137rqMjAysXbs2t3dw9erV0apVK4SFhaFz586ldv4XNzc3uLm5afVWyHsXXyq67/OiPpcB4vksbxwl9XXaM1POa5ac0wztn3Ojxt48ePAAu3bt0lpX2HDIHG3btkW1atVw69at3HXLly/Hp59+mu8+o0eP1koK/vbbb/j000/z7c2i21Nbd25YXbpza5ky3C9H+fLlTd6ntCkt16F5FfV7xdrkcjlq1aqFWrVqYejQoQCAc+fO4auvvtIayZTjww8/xKhRo/QSsyqVSq8ntLG974ylO2TW3Gsm3f0MDcXNj+40OYXJOw8qAK35BS2RX8y//fYb2rZtq3UOvH37Nr744gt88cUXcHJyQqNGjdC2bVuEhYWhY8eOVhn2T/aB/UOJSgFDH7bnz5+X9Bi67Xl5eenNWWFttnidQOEXG7o9xQoaUqH73KhRowrtyn/27Fns3r1ba91XX31l9ITNQ4cO1Zvzbs6cOSZ9KTWlR4w19rcma//+FAoFtm7dipkzZ+Z7JzsyMhKrVq3C+PHjUa1aNbRo0QIrVqyw28SBNem+z6V+j9++fVuvF0u1atUkPYYxdF/n1atXDc6paK6srCy9XlK2eJ32zJLzkj2f0yyxcuVKrfOOn5+fScPcdJMiK1euLPDGTvfu3bV6St+/f18v0ZLj3LlzWueDMmXKFDpUU7d3malDhwHrFM0oaUrLdWheRf1esYWGDRtizZo12Lx5MxwcHLSee/LkCX7//Xe9fYyZ485Susl+c9+jujeGTEkKmtpL1ZS2TZGWlmZwfWhoKE6dOpXvMOfMzEwcP34c33zzTe6838OGDcO5c+esEifZFpOCRKVAw4YN9dZJWbFVEITcnlQFHdParP06DbVXtWrVQnuTDB8+XKsL/vHjx/W+jAPA48eP9YqDvPzyy4XGpDt/kru7u171usLoTsAcHR2tN7yjtLL27w8Q57uZM2cOoqKi8MUXX6B58+YFztF48uRJvPzyy2jcuDGuXbtm3AspIXTf59HR0QZ7iJjL0DnDHs5nWVlZuHDhgmTtX7hwQS/JaIvXScWLbqXe2NhYODg4QCaTGbXMnj1ba/87d+5g7969+R5PqVTqFf7Ir+CI7vr+/fsXmgzQHR5nTuJdymR9SVVarkPzKur3ii317dsXn3zyid56e43XHlnrPFJQ0Zfq1atj7969OHLkCCZOnKg3t21eaWlpWLt2LRo3boypU6fyvFfCMClIVAo0b95c78I3vzvt5jh58qRezxpTJmiXSlBQkN5QYd0edJZ48OABLl++rLXOmNfp7e2tV5nX0JeaVatWITs7W6ttY+aP0U0UNG/eXO+ObWGaNWumN7eb7gV2aWXt319e5cuXx9tvv40TJ04gISEB//zzD9577z107NjR4NwuERER6NChA+7du2fScYozQ0VppDyfGTpn2OJ8VlpeJxUfJ06csEq194J6XwP6vbV1izcA4hfq1atXa60rbOgwoN9DyZy5O60x32dJU1quQ3PY6r1iS5MnT9a7jrx586bedt7e3nrrpC6spDss3dw5LHXf24Zil4pu23///bdedXlzFt3ksiGtW7fGzz//jOjoaERFReG3337DhAkTULt2bb1tBUHA/PnzjTq/UvHBpCBRKeDi4qLXPXzXrl24f/++JO0bSpDoVroqKj169NB6fPXqVb3Je83122+/6Q3dMPZ16n6p0R1WAuhf7BlTYATQHyZhTtVahUKhN/+JlL2vijtr/v7y4+7ujueffx6ffPIJ9u7diydPnmDDhg16E3I/fPgQ77zzjkXHKk66d++uNyRbqi9KGRkZWLdunda62rVrIygoSJL2TdGuXTu9Xsi6PU8soft/5unpKflk71SyWCshsWXLlgK/tIeGhmpVy8zMzNSbw+zPP//U+swKCgpChw4dCj227nyAhnqBF8acfUqb0nQdCtjuvWJLbm5uetPWGLqOdHBw0EvGG0oeWkL3evb27dtmtaNbtMOaSUE/Pz+tx7a6Bg8KCsKIESOwaNEiXL58Gbdv38Znn30GX19fre1Wr14taccLsi0WGiEqJUaOHIl//vkn97FGo8HPP/9ssLu/KRISErB+/XqtdbVr19Yrd19URo4cqVeta8GCBWjZsqVF7apUKixdulRrnZeXl14Psvx07doVlSpVyr0AjomJwc6dO3MvWsPDw7V6/Lm5uWHgwIFGta07b0l6erpR++nSnXfExcXFrHZKImv+/ozl6uqKgQMHYuDAgZgyZQoWLFiQ+9zmzZuRkZFhcnW94qhChQro0qUL/v3339x1u3btwo0bNxASEmJR22vXrtXrsWDsEHCpOTo6YvDgwfjll19y1129ehV79uxB586dLWp73759eomMYcOGmVQJmkoXQwnz8ePHo3Hjxma199FHH+Hhw4cAxM+eDRs2YNy4cfluP2bMGJw8eTL38fLly/Hqq69qPc7r5ZdfNmpex6ZNm2o9Nucm4okTJ0zepzQqLdehtn6v2JLudWN+15FNmjTBnj17ch8fPXoUAwYMkCwO3cq/Fy9eRGZmpknVdAVB0BviXr9+fUniM6Rhw4Za15Fnz57FSy+9ZLXjGSswMBCzZs3C2LFj0apVK61E6erVq9GlSxcbRkeSEYioWBg1apQAIHcJCwszaf/MzEwhICBAqw1nZ2fh5s2bFsU1YcIErTYBCL/88kuh+wUGBmrt8+GHH1oUR14tW7bUalsmkwmHDh2yqM05c+bovc5Zs2aZ1MbMmTO19h8wYEDuc5MnT9Z6bsyYMUa3O378eK1969SpY1JcgiAIDx8+1Ht9q1atynf7Dz/80KLfX1hYmNb++/btM2l/3ViLgrV+f+ZITk4WHBwctI4ZERFh1WNKRfd3t2zZMpPb2LFjh147zz33nEVxJSQkCP7+/lpturu7C0+ePClwv3379unFEhUVZVEsOS5duiTI5XKttkNDQ4WsrCyz28zKyhLq1q2r1aZcLheuXr1qcbzWPK8bYunnoi5Lziu6fwemxmLpOdXa1q5dqxWfUqkU4uLizG7vtdde02qvTZs2BW6fmJgolClTRmufixcvCoIgCDExMYJSqdT6zL99+7ZRcURHR+v93sPDw016LbrvJ3v8erVs2TLJYzT1XG5v16EFseRcZuv3ii1VqVJFK9bnn3/e4HaffPKJ1naVKlUSVCqVZHEkJibqfXZu2rTJpDb279+v93dV0N+q7t+MqdcBv/32m9b+tWvXFjQajUltWNtPP/2kFWPjxo1tHRJJhMOHiUoJR0dHfPTRR1rrMjIyMHbsWLMni921axcWL16sta5mzZo261mTY86cOVqPBUHAhAkTzJ6z5MKFC/j000+11vn4+GD69OkmtaM7nPSPP/5AfHy8waFQpgw91b37fOnSJVy/ft2k2LZs2aK3ztaTdNsba/3+zOHu7q43PCY1NdWqx7Qn3bp1Q1hYmNa6Xbt2YdGiRWa3OW3aNDx69Ehr3YwZM6w6XKgwoaGhekUWLl++jA8++MDsNj/++GNcvHhRa92oUaNQs2ZNs9ukkk+3J16XLl30zkGmGDJkiNbjI0eOFDiE0NPTE3379tValzNkdOXKlVrzuXbq1AmBgYFGxREQEIA2bdporfv444+N2hcQPzt1309kWGm5DrX1e8VWzp8/j7t372qta9SokcFtBwwYoNWT9/79+/kWEDKHp6en3vt6/vz5JrUxb948rcc1a9Y0WEVbKi+88IJWz8orV65g69atVjueOapWrar1uDRdd5Z0TAoSlSKjRo1Cp06dtNYdOHAAQ4YM0bqgNsaxY8fQt29frapWcrkcv/zyi8lFLqTWsWNHvaTMlStX0L17dzx9+tSktm7cuIHnnntOb2jtDz/8YHKyICQkBG3bts19nJWVhTVr1uQml/LbrjDPP/+83rq3337b6P3j4+Px2Wefaa2rXLky6tSpY3QbpYE1fn+mvu9yxMXFITY2Vmud7txYeQUFBWlVNTRmri17t2jRIpQpU0Zr3eTJk7FhwwaT25o+fTpWrlyptS40NNQu5mr85ptv9OYJ/eKLL/Ddd9+Z3Na8efP0bnD4+/vj66+/tihGso3Zs2frVSw1d+6sgty/f1+vKIRuosJULVu21Jurs7B52HQnts8p7mTpfK55hyEDwLZt2/QSTYbcvn0bU6ZMMelYOfbv36/3u7PnIhJSKenXofbyXjFV//798ddff5m9v1qtNnijvFevXga3r1WrFvr06aO1bvr06ZLOzzl16lStx/v27dP7nM/PX3/9hc2bN2utmzZtmmSxGeLr66t3LnrllVcQHR1tdpt53xt5mXvtqVs8p6DrTipemBQkKkVkMhnWrFmDypUra63fsmULOnToYFSlNI1Gg7lz5+K5557Tu0P0ySef2E31yvnz56NBgwZa644dO4YWLVoYPWfQmjVr0Lp1a73eQ+PHjzd7ng/dLyvLli3Tuztq6heaqlWr6l14bd26Fa+99lqhH/wPHz5Ez5499arX6l5MkUjq39/27dvRrl07bNmyxeiLNLVajddee02r0EnVqlWN7hlTUtSsWVPvi7tarcawYcPwzjvvICMjo9A2YmJi0L9/f70Em7u7OzZt2mQXc+z5+vpi/fr1UCq1p4GePn06xo4dq1doyJDk5GRMmjQJr7/+utZ6pVKJ9evXW9SLhUq+lStXahXZcnJy0uu1Z47BgwcXeBxduj0AHz16hNmzZ+Py5cu56zw9PdGvXz+T4hgyZAhatWqltW7SpEn46KOP8u3BtmfPHoSFheHBgwelYi5XqZT061B7ea+YKjw8HL169UKzZs2wbNkypKSkGL1vfHw8Bg0apDVHICBWtNV9X+X1ySefaN3YS0lJQfv27XHo0CGjjpuWloYff/wRjx8/Nvh837599W5ujx8/Htu3by+w3ZwkdV4BAQEYNWqUUXFZ4u2330bFihVzHz969Ajt2rUz+v8kx+XLl/HKK6/ke2Nz5MiRmDRpkta5szBRUVH48ssvtdbpFg+i4ouFRohKGX9/f/z777/o0KGD1gfpkSNH0KhRIwwYMACDBw9Gy5Yt4evrC5lMhszMTNy+fRvbtm3DypUrDQ6VmTZtGmbNmmV2XKdPn9YrEGKKbt26ad1JdXFxwY4dO9ChQwetobSXL19GmzZt0KtXLwwZMgQdOnRAuXLlIJfLoVKpcO/ePfz9999YvXo1jh07pnecfv36YeHChWbHOWjQIEybNi33QvbMmTNaQyjkcjlGjhxpcrtffPEFdu/erVVkZN68edi/fz/+97//oWvXrqhQoQIA8c7h5cuXsWXLFsydOxdxcXFabVWvXt3qd0SLK6l/f4Ig4PDhwzh8+DC8vb3Ru3dvdO7cGY0aNUJISIhWUurBgwfYt28fvv/+e73Jr6dNm2bUpPolzfDhw/Ho0SOtHgpqtRpffvkl1q5dixEjRqB///6oUaMGXF1dAYiT0p8/fx4bNmzAmjVrkJSUpNWmq6srtm/frldF0RSrV682O9Hm5OSkl1ju0KEDVq9ejWHDhmklg3/99Vf8+eefGD58OAYNGoQ6derAw8MDgPgF6/Lly9i4cSNWrVqld3NDoVBg9erVesOwC1PQeVr3i2RB5/WaNWsa9YXijz/+wIMHDww+d+3aNa3HDx48yPd47u7uGD58eKHHI326Va9feOGF3L8zSwwZMkTrS+adO3ewd+/efCeul8lkGDVqlNbwXt3pQoYMGaLXg7gwcrkcy5YtQ7NmzXL/hjUaDWbPno2FCxeiZ8+eCAkJgbOzMx48eIDdu3fj7Nmzuft//PHHeOutt0w6Zmlmr9ehUrCX94q5Tp8+jTFjxmDKlCno2bMn2rVrh9atWyM4OFjrdSQlJeH8+fP4448/sGzZMq3REgDg7OyMBQsWFHhdUqdOHSxcuFDr8y42Nhbt27dHv379MGLECISFhcHLyyv3+bt37+L06dP466+/sGXLFiQkJOTbG1GpVGLNmjVo3rw5MjMzAYiVy3v16oWRI0diwoQJaN68OZRKJdRqNc6dO4elS5di0aJFWgnXnM/KnGsIa/L19cWWLVsQFhaWe2Pz7t27CAsLw/PPP4+RI0eiTZs2qFKlSu7/rUajwd27dxEREYFjx45h27Ztucm+yZMnGzxOWloa1q5di0WLFqFu3bro27cvWrZsiYYNG6JChQq5batUKly5cgVbtmzBDz/8oDUNk5ubm17vbSrGbDmhIREZT+oJ1SMjI4V69erpTaKbd3F0dBTKli1b4DZyuVz4/PPPTT6+7oS8li5btmwxeJzHjx/rFbXQXRQKheDl5SXIZLICt5s6daokEyG//PLL+R6jW7duZre7detWQaFQ5Nu2s7Oz4OPjozUhu+7i5+cn3Lhxo9BjlcZCIzmk/P1t2bKlwL85V1dXwdfXV3B2di7wmGq1usDj6L7fLD1/WEI3fnMKjehasWJFgf9HAAQPDw+9QgW6S+XKlYXTp0+bdGxDhUYsWTw9PfM91j///CN4eXkV+jfj6upa4DZly5YVdu7cadb/tVSvc9SoUUYdr7Dzt7FLYGCgya/NFLYoNKK7DyBdkZscx44d0zvGunXrJGu/Vq1aWm0PHz68wO1v3bpV4Gf18ePHzY7l6NGjgoeHh0l/VyNGjBDUarXWOmdn50KPZei8IcW5MD/2UGhEl62vQwtiTqERe3uvmMKYa3JHR0fBx8en0M9RZ2dn4d9//zX62N98841eURDd9ry9vfO9di3snLdx40bByckp378dLy+vfK+dFQqFsHjxYrP+Dy05F+/cubPAz3qFQiF4e3sL7u7uBZ4PJ0+ebLD9F198scD3k5eXV4H/L3K5XFi5cqXZr4/sD4cPE5VS1apVw8mTJ/Huu+/me1c9KyurwOIcjRs3xtGjR+1i3q38+Pn5Yc+ePfj++++17jbmpVarkZCQkO/cG8HBwfj7778xb948vSF85ihoeKkld91efPFF7Nu3T2/umRwZGRl48uRJvsNUw8LCcPLkSQQHB5sdQ2kg5e+vsN59qampiIuLMzgUViaTYcKECfjjjz8gl5fuj/ORI0fi3LlzBfaaSE5O1upJm5dSqcSECRNw4cIFNGnSxFphWuz555/HxYsXMWjQoHz/dlJTU/Od/Fsmk2HAgAG4dOkSunbtas1QqYTQnbvM1dU135455tAdFrllyxYkJyfnu33VqlXznRM1NDQULVq0MDuWVq1a4fjx40YNP3V0dMTHH3+MFStW6PWQLVu2rNkxlCYl7TrU3t4rpujRowc8PT0L3CYrKwtPnjzJ93MUANq2bYtTp07hueeeM/rY06dPx7Zt27SGzeaVkZGB+Pj4fK9dC7v+GTBgAHbu3Kk3ZB0Qe9klJCRo9cDP4efnh61bt2LcuHFGvAppde3aFeHh4fmei9RqNeLj45GSkpLvdxdnZ+d8RzwUdO2Z83+S3/+Lr68vfv/9d7OnUSL7VLq/RRCVcs7Ozvj0009x+/ZtfPLJJwgNDS10H1dXV/Tr1w/bt29HeHi4RRfgRUWhUOD111/H7du38f3336Np06aFJmMcHR3RrVs3rF27FlevXsULL7wgWTzt2rUzWMEsZ/iopW1funQJP//8M5o0aWL069y2bRv27t2bb0KR/iPl7+/FF19EeHg4Zs+ejXbt2hk17M3d3R0vvfQSTp48iUWLFtm8sI+9qFmzJnbt2oUjR45g1KhR+d4EyCswMBBvvvkmrl27hkWLFhWLL/MVK1bE+vXrERERgcmTJxs10be/vz9eeeUVnDt3Dhs3bsz3yxdRXhkZGVi/fr3Wul69emlVyLSU7txdaWlphRYLyu/GjBRV32vXro0DBw7g33//xbhx4xAaGoqyZctCqVTC19cXbdu2xUcffYTIyEi8//77kMlkenOaGXPuIVFJuQ611/eKsRYsWIDY2Fjs2rULb7/9Ntq0aQMnJyej9vXy8sKIESPw77//4uDBg6hbt67Jx+/ZsyciIyPx3XffoV69eoVuHxgYiClTpiAiIgIBAQGFbh8WFobr16/jiy++QI0aNQrcNigoCB988AEiIyPRs2dPo1+D1KpWrYoDBw5g//796NOnj1HD0L28vNC3b18sXrwYDx8+zLcQ0urVq7F161aMHz8eNWvWNGr6mZCQEMyePRs3btyQZJ5Msi8yIb/0MhGVSo8ePcLZs2cRFRWFpKQkqFQquLi4oEKFCqhRowYaNmwoSW85W0tISMCZM2dw69YtJCQkIDMzE2XKlEG5cuUQEhKCRo0alYjJw5OSknDq1ClER0cjMTER6enpcHd3h5eXF2rUqIFGjRoZfeFH1qdSqXDt2jVERkbi3r17SElJgVqthpubG3x9fVGnTh2EhobaRQEMe6fRaHD58mVcuXIF9+/fR2pqKuRyOdzd3REYGIh69eqVmCT4jRs3cPHiRdy9eze315K7uzuqVKmC0NBQ1KxZ08YREpVca9as0Zqvsl+/fti0aZMNIyreSst1qL3Lzs7GrVu3cP36dTx48ADJycnIyMiAi4sLPDw8UK5cOdSvX98qn6MPHz7EyZMn8fjx49x5rz08PBAYGIg6depYfMyoqCiEh4fj8ePHSExM1Ho9lswnbE1qtRpnz57FzZs38eTJEyQmJsLJyQnu7u6oXLkyatWqhapVq5o1ciQhIQFXrlxBVFQUYmNjkZqaCqVSCXd3dwQEBKB+/fpGJV+p+GJSkIiIiIiIyAyDBw/W6rH1xRdf4O2337ZhRERERMbj8GEiIiIiIiITXblyRa9XoNQVYYmIiKyJSUEiIiIiIirVsrKyTNo+Li4OAwcO1JqMv1mzZnZdrIiIiEgXk4JERERERFSqde7cGa+//jrOnTtX4HYajQZbt25FkyZNcOnSJa3n3n33XStGSEREJD3OKUhERERERKVaw4YNcf78eQBAQEAAmjVrhtq1a8Pb2xsKhQKJiYm4du0aDh48iHv37untP3bsWCxZsqSowyYiIrIISzeVcHfu3MFff/2V+7hatWpwc3OzYURERERERPYlNTU19+c7d+7gzp07Ru/btWtXDBs2DIcPH7ZGaEREREZ7+vQpbt26lfu4Z8+eBVaQZk/BEm7hwoWYPHmyrcMgIiIiIiIiIqIitGDBArz66qv5Ps85BYmIiIiIiIiIiEoZJgWJiIiIiIiIiIhKGc4pWMJVq1ZN6/GCBQtQv359G0VDRERERERERETWEBERoTWFnG5OSBeTgiWcblGR+vXro23btjaKhoiIiIiIiIiIikJhhWY5fJiIiIiIiIiIiKiUYVKQiIiIiIiIiIiolGFSkIiIiIiIiIiIqJRhUpCIiIiIiIiIiKiUYVKQiIiIiIiIiIiolGFSkIiIiIiIiIiIqJRhUpCIiIiIiIiIiKiUYVKQiIiIiIiIiIiolGFSkIiIiIiIiIiIqJRhUpCIiIiIiIiIiKiUYVKQiIiIiIiIiIiolGFSkIiIiIiIiIiIqJRhUpCIiIiIiIiIiKiUYVKQiIiIiIiIiIiolGFSkIiIiIiIiIiIqJRhUpCIiIiIiIiIiKiUYVKQiIiIiIiIiIiolGFSkIiIiIiIiIiIqJRhUpCIiIiIiIiIiKiUYVKQiIiIiIiIiIiolFHaOgAiIiKyPyq1BnuvPkZk7FOkZarh4qRAdT83dKpVDg4K3lMkIiIiIirumBQkIiKiXI+SM7D6xB2sOh6N+NQsKOQyyAAIANQaAd6ujnipZSCGtwiAv4ezrcMlIiIiIiIzMSlIREREAIBjkU8wbsUppKvU0AjiOnXOD8/Ep2Zh/t4bWHroFpaMaoZW1X1sECkREREREVmKSUEiIqJiJjNbjXsJ6chWC1CpNchSa6DK1iBbI2j9rFJrkJWtgUotIFvz388qtQbZag2ynv2sUmtwLyEd+64+hlD44aERgHSVGiOWnsDKsS2YGCQiIiIiKoaYFCQisjLOzWY/1Jr/kmi5CbVsMSmWrRG0flZl62yX52fVs4RatoGfVXm2UamFZ/v9t37xyKZwdlBY9Dqi4lLR7YdDEv2vmEfsQChg3G+nsHd6Bw4lJiIiIiIqZpgUJCKykpI+N5vmWa+0nASaXrJN52dVPkm0LLWAnvUqwMvV0aJ4UjOz8eKCI896wT3rMafzs2BMNzgry1RpLE4K2ksyWSMA6VlqrDlxB288V8PW4RARERERkQmYFCQisgLT52ZriiaB3lo9zNydlRYnjwDgxz038DQz2+xeb1nZGmRrnvV0y+k9pxH0Xo8lmgR4WZwUVMhluPn4qUQRWY9Ko7G4DQe5fSQFATExuPjQLYxsHQgfVydbh0NEREREREZiUpCISGLHIp9gxNIT0AgCCsubaQQgNUuNoYtP6D23ZGRTdAn1tzieZUdvIz41y+J2rEmlliBRZie95wojyWtVyiSIRDppWWq0+WIvJrSrhtFtqlqc4CUiIiIiIusrHt+giIiKiUfJGRi34pRRCcHCSJE8AgAHhX0lkAzJlqD3nEIug9z+XypU2Zb3sLTHBGiGSoN5e2+i7Zd78fmOK4h7mmnrkIiIiIiIqAD2962CiKgYW33ijtaQYUtkSZYUtP9TfZYEiTIAUBaD11rShg/rSs1SY9GBW2j75V589OclZEv0d0xERERERNKy328VRETFTFa2Gr8ejpIkIQgA2WppGioOSUGpekU6lpLXam/Dhw3JUGlw49HTYpGoJSIiIiIqjXilTkQkgbvxaei38CieZmZL1mZpGj5cql5rCR0+bMiUTsG2DoGIiIiIiPLBQiNERBZQqTX49XAUfth9A+kqteRtS6E4JJBUpalXpATDh5XFYPLE5kHeaFnNx9ZhEBERERFRPpgUJCIy05k7CZi1+QKuPkyxSvtZpSlRVpoSoNmWv1aZTAYHhUyyZKo1sJcgEREREZF9Y1KQiMhEyRkqfP3PNaw6EQ3BijkZqQo0FIshtaXqtUrzR+PmpES2WoBSIYODQv5syfOzUg4HuSz3Z0eFDEr5s/UKGRzkcjgoxedV2RqsP30X2WoBUkTXoEpZtAvxlaAlIiIiIiKyFiYFiYiMJAgC/r7wEB/9eQmPUzKtfrxS1XvOhq9VJhP3c3yWVFPm+dlBIX/2OOdnWZ5txcd5f3ZQyOH4LOmmlGv/nJOYCy7nJslrPftBV0naydGjfkWMWHoCGkGwuFjO1I7BkMnsP0FLRERERFSaMSlIRGSEu/Fp+GDbRey7Fltkxyyuw4cd8yTItHuv5dOjTSGDv4ezJMf+vF89ZGVr4KCUQyn/L0mX92fdZJ6iGMzPVxRaVffByrEtMO63U0jPUpudGKxdwQOda5eTNjgiIiIiIpIck4JERAWwZiERY44thc61yyHQxyXfhJxRPyvlWsNNtX7O26tOLrNpD7GmQd42O3ZJ0Kq6D/ZO74A1J+5g5fFoxKdmQSGXQQZAAKDWCPBxdcSQ5lVQxkGBNSfu4EFShlYbUztJ10swK1uDo5FxCKvhx56HREREREQSY1KQiCgf1i4kkpdcBjg7KLBtchtU8iojDjeVaH68ka2CJGmHSgd/D2e88VwNTOkUjH1XHyMyNhWpmdlwdVKiup8rOtYql9v7dEL76th85h4W7o/Enfg0BJdzQ7c65SWLZfOZe3hn8wXUqeiBqZ2C0TW0POTs2UlEREREJAkmBYmIdBRVIZEcchkgl8nw68vNEOLvbv0DEhnBQSFH10ISfI5KOYY0D8CAJpXxx/kHKOviIFnSLlutwcL9kQCASw+SMWnVGdTwd8PkjsHoWb8ih30TEREREVmISUEiomesVUhEiWx0kp9FdVkMXGQZSBOcESlUwF5NI2hkSpRxVGDpqGZoWc1HsmMSFSWlQo5+jStL2uYf5x/gTnya1rrrj57itXXn8MPuG3i1Q3X0aVSpWBTSISIiIiKyR0wKEhHBOoVE6num4VW3Q2j+ZAu8kYxsQQ4BMsggQCnTIB4euF5lEKq/MBV+FZkQJMqh1giYv+9mvs9HxaXizd8jMHfPDbzSoToGNKkMJ6WiCCMkIiIiIir+eHudiEo1lVqDRQci0fX7g5IlBJVyGT5vlIhtwmvoFr8K3kgW18s0cJCpoZSJBUS8kYyW95bBb3lrIOqQJMcmKgl2XIzBrdjUQre7l5COd7dcRIev92P5kShkFHExICIiIiKi4oxJQSIqtTJUarw4/wg+33FVssrCTQK9sLe/AkOvTYNMlQ4IhbQrqAFVOrCyj3ZisCgmMySyQxqNgPl78+8laEhMUgZm/3kZbb/ch18ORiI1M9tK0RERERERlRwcPkxEpZazgwINqnjickyyxW15OCvxzgu1MaSWEvIFTQFBIy7GyNlu7RBgymnAowLwx1Tg+k7AzR9w9xf/dfMH3MsDbuUAt2f/upcHHF0tjp/IXuy68sjsit9xTzMx5++r+Gl/JMa2rYqRrYPg4ewgcYRERERERCUDk4JEVKq93a0Wdl1+hLinWWa30btBRbzXszbKuTsD++YAqgzjE4I5BA2gSgPClwMdZwIpMUDqY3F5dKHgfR3d/0sQ5iQM8yYSc5KJZbwBOTuIk/0SBNN7CRqSkKbCN/9ex6KDtzC6dRBGt6kKL1dHCSIkIiIiIio5mBQkolKtrIsj3u8ZitfWnTN53wBvF3zapy7a1/ATV6hVwKmlhQ8Zzo+gAU4vBdrPAFIeGb9fVgoQnwLERxa8nVwJuJYroOdhnl6JSifzXgORBfZfj8WF+0mStZeSkY15e29i6eEovNQqEOPbVYOvG/+2iYiIiIgAJgWJiNC7QUX8Hn4Ph27EGbW9Ui7DhPbVMK1zCJwd8lQ8vb4TSDOujXylxgI3/gWempAUNJYmG0h5IC6FcS77LGHorzOEOU8vxLIBgEMZ6eOkUuvyg2Qo5DKoNdLOqZmapcaiA7ew4uhtDG0egIntq6O8p7OkxyAiIiIiKm6YFCSiUk8mk+HTPnXR9fuDyMwueNhvk0AvzOlbDzXLu+s/GXcdkCsAjQVFS2QK4PFVMTloSxmJ4hJ7Nf9thq4Dar5QVBFRKTC5YzB61q+AhfsisenMPWRLnBzMUGmw7MhtrD5+BwObVsYrHaqjspeLpMcgIiIiIiouOLkUERGAQB9XTOscku/zHs5KzOlbDxsnttJPCF7dDqwdCmSmwOLTqkwuziOIYlB92M1fmnYubwOijwJPIoHMp9K0ScVWoI8rvhxQHwfe6ogRLQPhqJT+UiVLrcHqE3fQ4ev9eHPjeUTFpUp+DCIiIiIie8eegkREz4xvVw3bzt3H9UfaiSmtQiJ5CQJw8Gtg32fi49Q4ACYWGNElaMR2iwP38pa3kZUGbBipvc7RrYCCKf7/zX/o4sPCKSVYpbJl8EmfupjSKRi/HLyF1SeikaGy8P2lI1sjYGP4PWw6cw+9GlTElI7BCPE30AuYiIiIiKgEYlKQiOgZR6Ucc/rWw4CfjwEAqniXwad96iEsp5BIXplPgW2vir3cctw7aXkQghpw9rC8HauTAa4G/l9MZWjuxKynQPxTIP5WISEoniUPdQum5FRiLv/f8w6cP6648vdwxvs9Q/FKh+pYejgKvx29jdQsC4boG6ARgG3nHuCP8w/QrU55TOkUjDoVPSU9BhERERGRvWFSkIgoj6ZB3hjZKhBuTkpM7RSCMo4K/Y0SbgPrhgOPLkofgKsf4F5R+nal5uIDKBwsb+fpY/P3FdRASoy4xBSyrbOnfs/DvIVUcnohOpcFZDLzYyKr8XVzwtvdamFi+2pYduQ2lh2JQnJGtqTHEARgx8WH2HHxIbrULocpnULQsEpZSY9BRERERGQvmBQkomLrzJ0EfLb9CuYNbYRKZaWrgvtR7zqQ5ZcYijoIbBgFpMdLdrxcMjnQdKzlFYyLghRDhwHg6UNp2ilMRpK4xF0reDuFk061ZX/AszLQ7n9FEycVqqyLI954rgbGtauK345FY+nhKMSnZkl+nN1XHmP3lcdoF+KLqZ1C0Lyqt+THICIiIiKyJSYFiajYSUpX4eudV7H6xB0IAjD7j0tYPLKpZO0bTAgKAnBqCbDjbbGHmtRkcsDBBWjyMnDoG+nbl5pbOWnaSTEwfNiW1JlA0h1xyeHBpKA9cnd2wOSOwRjdJghrTtzBooO3EJuSKflxDt2Iw6EbcWhR1RvTOoegdXWf/G8aEBEREREVI0wKElGxIQgCtl+IwUd/Xtb68r/r8iPsvPQQz9eRqPearuws4O/pwJnfrNO+TC4uw9YDHhWALrOB5hPE+fZSHom96XJ/frakPAQyEq0TjzHcpOopaGdJQUPcJaqyHLlX/BvSGr5cjoVTLOTiqMS4dtXwUstAbDh9Fz/vj8SDpAzJj3MiKh7Dl5xAq2o+WD2uBeRyJgaJiIiIqHhjUpCIioW78Wl4f9tF7L8Wa/D5D7ddQptgX7g5SXxae/oYWD8CuHvczAZkAAqoJpzTQ3DYeiCorbjOyR3wqykuBcnOfJYkfCwmCZ8+zPPzY/FxyiMg9TGgkXbuNckSZUU1fNgSUiVAH14ELm3J/3m5EnAtl6dQim4F5iIunKJWAdd3AnHXgaxUwNEV8K0B1HhemvkkJebsoMDIVkEY0iwAm8/cw8L9kbgTnyb5cWqWd2dCkIiIiIhKBCYFiciuqdQaLD0chR92X0eGSpPvdg+TM/Dtv9fwYa860h38wVmxoEjyfQsaEYAyXkB6glgtVyYHBI04BNnVT5xDsMnLYg9BUymdgLIB4lIQjUacAzGnh2Fub8NH+onErBTjji1ZT0ELCo0UFamGShfWK1KTDaQ8EJdCC6eU1Z/7MG/hlJykojmFU5JjgPBlwKml4vyWcgUAOQANoFEDLr5As7FAk9Hm/d1amaNSjiHNAzCgSWX8cf4B5u+7iVuxqZK07aCQYWJYNUnaIiIiIiKyNSYFichunbmTgFmbL+DqQ+MSVSuO3kbfRpVQv3JZyw8esRH4YwqQbcEwRAcXoM9CoFZP4Ma/Yo+rzKeAk5vY4yqka9H0uJLLAVdfcfEvJGmalard0zA3YfhIewizVIVGUopBT0HJiqpIOFQ6I1FczCmcYqgXoms5QKEEog4BawcDqoz/5s7UqAHkmUczLQ44+A1wbD4wdD1QtZ10r0tCSoUc/RpXxosNK2HHxRjM33vT6HNJfgY0qYIKntIVNSIiIiIisiUmBYnI7ugWEjGWRgBmbbmAra+2gVJh5txsGjWw5yPgyFzz9s/hGQAMWQ1UqC8+rtUDQA/L2iwKjq6AT3VxKQrFYU5ByYqq2CABaqhwikEycdh61lPxoZB/r1zxeTWgSgdW9gFGbLXbxCAAKOQy9KxfEd3rVsCuK48wf+9NXLifZFY7r3YoovcFEREREVER4IzmRGQ3BEHAXxEP0OW7A1h13LSEYI6L95Px27Fo8wJITwTWDLY8IRjYFpiw77+EIBkmCGLPRb9a4jBXe1UqiqoIQGay+DspLCGYu4tGXNYOEYcc2zm5XIbn65THH1PaYNnoZmgcUNak/fs0rIQq3i7WCY6IiIiIyAbYU5CI7EJhhURM8e2/19CtbnlULGvCML/Y68C6ocCTm5YdvNk4oNsXdlmIwe7IZMCIPIU3Ciyckmf4sjUKpxTETaqiKvacFMxhYiZe0ACqNCB8OdBxplUikppMJkPHmuXQoYYfjkU+wY97b+LYrSeF7ANM7shegkRERERUsjApSEQ2ZWwhEVNkZmtw6nY8XmxYybgdrv8LbBor9pQyl1wJdP8GaDra/DZKO1MLp+RNFlpaOKUgUlRaVqUDGaYPWS0WBA1weinQfsZ/yfC0eCA1Vpw709RCJ0VEJpOhdbAvWgf74vTtePy49yYOXDd8U6Jn/Yqo5udWxBESEREREVkXk4JEZDOmFhIxRpNAL3zerx5q+LsXvrEgAEd+AHZ/BJN7SOXl4gsMXgkEtja/DTJe3sIpqFvwtplP/+t9mG/hlIdAahzy/RtwlWBOweJQZdkSqbFiMZ1az+bNvPIH8OdrYoXtwDZAUFvxX79a4u/PzjQN8saKMc1x/m4i5u+7iV2XtXt1TukYLNmxHidnYNXxaIxuUxVero6StUtEREREZComBYmoyJlbSKQgHs5KzOxeG4ObVoFcbkTPpKw04I+pwMXfLTtw+frAkDVA2SqWtUPW4eQmLoUVTlFni4mt3GThswRiZhKglCBxUyyGDltAphCra+cU07l9WPw3NRa4vFVcAMDFR0yeB7UTk4TlQu0qSdigSlksHtkUlx8kY8H+m/j7Qgy6hvqjZnkjbjIY6ZeDt7DkcBSWHo7CS60CMb5dNfi6OUnWPhERERGRsZgUJKIiIwgCtl+IwUd/XkZsSqZk7b7YsCLe6xEKP3cjv1gn3gXWDwdizlt24Lr9gd7zAUcWHyj2FErAo4K4WIMtKg8XJZlc7JUJiD1wbx8xvF3aE+DKn+ICAGW8xORgYBsgqA3gXxeQK4om5gKEVvTAgmGNcfNxCuQSDn9+8jQTq0+IlaBTs9RYdOAWVhy9jaHNAzCxfXWU93SW7FhERERERIVhUpCIioSUhURyBHi74NM+ddG+hp/xO0UfAzaMEHswmU0GdP4AaPuG3c6XRnamfD2gx3f/DWNOeaQ9H2JRFk6xBkEj9sgEgPhbQMoD4/ZLTwCu/iUuAODsCQS0FocbB7URe+LaMEkYXE66HoIAsPRwFNJVaq11GSoNlh25jdXH72Bg08p4pUN1VPbijQYiIiIisj4mBYvY06dPcenSJVy9ehVPnjxBRkYGypYti3LlyqFp06YICgqydYhEkrJGIRGlXIaJYdUwtVMInB1MSBicXgb8/SagUZl/cCcPoP8SoMbz5rdBpY93VcB7rOHnNBoxOfb04X/Dlg0lDlMeSVM4xRoEtVhUBACi8+klaIyMJOD6DnEBxPdbQCsxQRjYFqjQQOzVWQwlpmXht2PR+T6fpdZg9Yk7WH/qLvo2qoTJHYMR5OtahBESERERUWlTPK+si9jQoUOxbt06rXWBgYG4ffu2UfufOHECW7duxZ49exAeHg6NJv/ESGBgICZNmoSJEyfCy8vLkrCJbM4ahUSaBnphjrGFRHKoVcA/7wCnllh2cJ9gYMhawK+GZe0Q5SWXA64+4uJfp+Bts1Lzr7ScN5GYGguLiueYytUPCOkq/pzf0GFzZCYDN3aKCwA4ugMBLZ4NN24HVGz4X8VjO7f86G08zSy8R2i2RsDG8HvYdOYeejeoiMkdgxFiyvmOiIiIiMhITAoW4s8//9RLCBrr3Llz6N+/P27dumX0PtHR0Zg5cybmzp2LZcuWoVu3bmYdm8iW7KKQSI7UOGDDSMt6LwFAcBeg/1KgTFnL2iGyhKMr4F1NXAqiWzhFK5GY5+eUR4A6Z35PGcxKJMrkQNOxYnJOEP4rMmINWSnAzd3iAgAOrkCV5s+GG7cFKjaWpjCMxFIyVPj1cJRJ+2gEYOu5B9h2/gFeqFsekzsGo05FTytFSERERESlEZOCBUhKSsIrr7xi9v737t3LNyHo6emJ8uXLw9PTE3FxcYiKioKQJ3vy8OFD9OjRA6tXr8aQIUPMjoGoKNlNIZEcMRHAuuFA0h3LAmg9Degy2y4KIBAZxdjCKYIgDtl9dBFYPRDIzhDnBzSWTA44uABNXhYfJ0YDyffMDttkqlTg1j5xAQBlGe0kYaUmgNL2lX1XHo9GcoZ580YKAvD3hYf4+8JDdKldDlM6haBhlbLSBkhEREREpRKTggV48803cf/+fQCAq6srUlNTLWqvZcuWeOmll9CxY0eEhoZqPRcbG4vFixfjs88+Q1paGgBAo9Fg5MiRqFmzJho1amTRsYmszW4KieS4tAXY+iqgSjM/AKUz0PtHoP4g89sgsmcymdj7NagtMGwDsLKPuN6YxKBMLi7D1v+XfLRmL0FjZKcDUQfEBRDfw5Wbia8vsI34s0PRVvhNy8rGkkOm9RLMz+4rj7H7ymO0C/HF1E4haF7VW5J2iYiIiKh0YlIwH/v378eSJeL8Y3K5HB9++CHeeustk9uRy+UYNmwY3nnnHdSpk/9cUX5+fpg1axZ69uyJjh07Ij4+HgCgUqnw+uuv48CBA+a9ECIrs6tCIoBYtGHfZ8ChbywLwr0iMGQ1UKmxZe0QFRdV2wEjtgJrhwCqdLF4SH5yeggOWy8m3HJIOZ+gFLIzgNuHxAUAFE5A5aZA45FAg6Lphb/mxB3Ep2ZJ2uahG3E4dCMOLap6Y1rnELSu7gMZK6ETERERkYmYFDQgPT0d48aNyx3OO3XqVDRr1szkdmrUqIGIiIgCk4G66tevj2XLluHFF1/MXXfw4EHcvHkTwcHBJsdAZE12U0gkR0YysHnCf5VLzVWlBTBoJeDub1k7RMVN1XbAlNNA+HKxME9aHCBTiElAQSMmCl39xDkEm7ysPzzZryZQsREQc960YchFRZ0pzi9arWORHdLHzREVPZ3xIClD8rZPRMVj+JITaBRQFtM6haBDTT8mB4mIiIjIaEwKGvD+++8jMjISABAQEIBPP/0Up0+fNrmdGjXMq1Dau3dvhIaG4vLly7nr/vnnH0yZMsWs9oiklq3WYPafl+yjkEiOJ5HA2qFA3DXLAmk0AujxrV3MQ0ZkEx4VgI4zgfYzgBv/AnHXgcyngJMb4FtDrDKcX8Xftq+LS0YScOcEEH1YHFL84FzBPQ+LWt7ejVbWt1Fl9KhXEZvP3MPC/ZG4E2/BlAb5OHsnEaOXn0LdSh6Y0jEEXUP9zTuPEhEREVGpwqSgjlOnTuGHH37IfbxgwQK4ubkVeRzt2rXTSgreuWNhoQQiCSkVcsSnZkmWEDS7kEheggCkPDR/f5kC6PYF0Hy8OM8aUWmncABq9QDQw/R9nT2BGl3FBQAyU4C7J8QE4e0jwIMzgMa8whsWUzoX+bQAjko5hjQPwIAmlfHH+QeYv+8mbsVaNk+xIRfvJ2PSqnDU9HfH5E7B6FGvAhRMDhIRERFRPpgUzEOlUmHs2LFQq8XeDAMHDkTPnj1tEouXl5fW46SkJJvEQZSfD3vVwcHrcXiaaf4Xe4sKiejyDQYG/AqsGWj6sMUy3sDA5UC1MMvjICJ9Tu5AcBdxAYCs1GdJwiNiovB+OKBRFU0sVZpL0xNYowaynooJUCMpFXL0a1wZLzashB0XYzB/701Jp1/Ice1RCqatPYsfdl3Hqx2D8WLDinBQyCU/DhEREREVb0wK5vH555/jwoULAICyZcti3rx5Noslp+pxDh8fHxtFQmSYv4cz3upWEx9su2TyvhYVEilISBegy2xg1wfG71OuDjB0DeAVJF0cRFQwR1egeidxAYCsNODeKTFBGH1E/FktbXGOXIESDR1+GAEs7gSUrwcEtROrGwe2Asp4FbqrQi5Dz/oV0b1uBey+8gg/7r2JC/elv/l3Ky4VMzaex9w91/FKWDD6N6kEJ6WE51wiIiIiKtaYFHzm8uXL+Oyzz3Iff/nllyhfvrxNYhEEAYcPH9ZaZ+78hETWNLxFIDaduY/zdxON3seiQiLGaD0NeHgRuLCh8G1r9wL6/CzOlUZEtuPoIvbUzemtq0oH7p0WE4S3D4tJwmyJCnVINZ/g7SNir+SY8+JybD4AGVC+rph4DGojJgpdvPNtQi6XoWud8ngu1B8Hrsfix703ER6dIE18edyNT8esLRfw494bmNi+GoY0D5D2hgwRERERFUtMCgLQaDQYO3YssrLEXgnt2rXD+PHjbRbP/v37ERUVlftYJpOhW7duNouHKD8KuQxz+tZF7/lHoNYUPMGgxYVEjCWTAb3nicURYs7lv12HWUD7NwE5h9QR2R2HMmIl5KrtxMfZmeIQ49vPCpfcPQlkp5versIJqNREmhijjxhYKQAPL4jLiZ/EVeXqiAnCoLZiktDVV28vmUyGDjXLIayGH45FPsGPe2/i2K0n0sSZR0xSBmb/eRnz90ViQvuqGN4iEK5OvBQkIiIiKq14JQhg3rx5OH78OADA0dERv/zyC2Q2KjSg0Wgwc+ZMrXXdunUzqddiZmYmMjMzAQCpqdJPZE6UV52Knhjbtip+OXgr3236NKyIdy0tJGIKhzLAkDXALx2A1Mfazzm6AX0XAbVtM18oEZlB6QQEthaXsLeA7CyxWEnOcOM7xwGVEVV9KzcDHJwtj0ejzicpaMDjS+Jy8hfxsV/t/3oRBrUF3MrlbiqTydA62Betg31x+nY8ftx7Eweux1oer464p5mY8/dV/LQ/EuPaVcOIVoHwcM6nojQRERERlVilPikYFRWF9957L/fxzJkzUatWLZvF88033+DEiRO5j+VyudawZmN8/vnn+Oijj6QOjShfr3cJwfaIGNxP1O65E+gjFhJpFyJBIRFTeVYCBq8Elvf8r4BB2UBg6DrAP7To4yEi6SgdgYCW4oIZgFoFPDgH3D70X5Iw66n+flINHX50Ccgwcw7A2CvicmqJ+Ni3xn8JwqC2gLt4E7BpkDdWjGmOiHuJ+HHvTey6/Eia2PNISFPh653X8FdEDP6e1tZmN0SJiIiIyDZKfVJwwoQJub3patWqhVmzZtkslkOHDuHdd9/VWvf666+jUaNGJrUzc+ZM/O9//wMAHDt2jEOPyepcHJX4+MU6GLviNACxkMiksOqY0inYtvNWBbQEen4H/DEVqBomVhguYH4vIiqmFA5AlWbi0u5/gDpbnOcv+tlw4zvHgcxksYeeFIztJWiMuOviEr5MfOwT/F+SMLAN6leuhMUjm+JKTDLm77uJvy/EQCh4tgaTDWtehQlBIiIiolKoVCcFly5dit27dwMQh+z88ssvcHR0tEkst27dQr9+/ZCdnZ27rmHDhpgzZ47JbTk5OcHJSRym6erqKlmMRAXpXNsf3euVx+PkTOsWEjFV45GAsydQswegKNWnPKLSQ6EEKjcRlzavicN9H0aIQ3elcPtw4duY68lNcTmzQnzsVRUIaoPaQe2woHsb3OwSgoX7IrHt/INC53I1Rjl3JwxsWsXidoiIiIio+Cm135BjYmIwY8aM3Mfjxo1Du3btbBJLXFwcXnjhBcTFxeWu8/f3x+bNm3OTe0RSSkpX4cc9N/Bqx2B4u0qXCP9qQAO4OCisW0jEHKEv2joCIrIluQKoaFqv+3xpNNL2FCxMQpS4nF0FAAguG4jvgtpiVvemWHq3EpZcVEOlNj85ODGsOisRExEREZVSpTYpOHnyZCQmJgIAypcvj6+++somcaSkpOCFF17A9evXc9d5enpi586dqFq1qk1iopJLEARsvxCDj/68jNiUTCSlq/D1wAaSte/GKpZEVNLFXgHSE2x3/MRo4Fw0fLEabwOY7l0JFxzqYUNsII5k18IdoRwA427M+Lg6YljzAKuGS0RERET2q1R+g9+4cSO2bNmS+3ju3LkoW7ZskceRkZGB3r174/Tp07nrXFxcsH37djRoIF2ihggA7san4f1tF7H/2n+VLDeG30O/xpXRqrqPDSPLI/MpsOcjIOwdwNVOYiIiysuaQ4fNoEy5j0a4j0YKAAogRvDBcU0t7FM3wh+a1gXuO65dNZRxZC9BIiIiotJKbusAbOHNN9/M/blHjx4YNGhQkcegUqkwaNAg7N+/P3edo6MjNm/ejDZtJJoInQiASq3BT/sj8dz3B7QSgjne3XoBmdlqG0SmI+E2sLQrcPIXYOMosZooEZG90WQDruVsHUW+KsieoK/iCHo5nChwO88yDhjRKrCIoiIiIiIie1Qqk4I5w4YBYPv27ZDJZIUuHTt21GojOjpab5tz584ZdXyNRoORI0fizz//zF2nUCiwZs0aPP/881K8RCIAQHh0Anr9eBhf/nMVGSqNwW1uxabi5/23ijgy3SAOAL90BB5fEh/fPgTstF0lcCKifLWaDMy4Dkw5DfT8Aag7AHCvYOuo9LTp/CJe6xwCD2fDg0LGtKnKKR+IiIiISjleDRYxQRAwYcIErFu3LnedTCbDkiVL0L9/fxtGRiVJUroKX++8itUn7kAwYv75BftuoleDCqjm52b94PISBODkYuCfdwBBp7fiyV8A/7pAk1FFGxMRUWFkMsA3RFyajhbPZfG3xKHF0UfEf5Pv2zREl5AwvFGhBsa1q4rfjkVj6eEoxKdmARDnf325dZBkxwqPjsfcPTcxtVMwmgV5S9YuEREREVkXk4JF7I033sDSpUu11s2bNw8vv/yybQKiEkUQBPwVEYOP/xILiRgrS63Bu1suYs34FpDJiqhycHYmsH06cHZl/ttsnw741QQCWhZNTERE5pDJAJ/q4tJklJgkTLj9X4Lw9hEg6U7RxeNcVrypAsDd2QGTOwZjdJsgrDlxB4sO3sKgppXh6eJgXFuCIL6+AszbcxMHr8fi4PVYtKzmjWmdQtCquk/RfZ4QERERkVlKZVJw27ZtUKlMm6/s/PnzmDFjRu5jf39/rFq1Smub4ODgAtt4//33MXfuXK11c+bMwZQpU0yKhciQu/FpeG/rRRy4rj9voDGO3XqCzWfuo3+TyhJHZkDKI2DDCOBuwXNeQaMC1o8AJuwDPIsgLiIiKchkgHdVcWn0krguIfpZkvCIOEVCYrT1jh/YGpBrzxDj4qjEuHbV8FLLQGRrjOhCDgCqDGBeQ6BiYyCoDRDUVkw2yv8rThJxL1Hrc+f4rXgcv3UCjQPKYmqnEHSo6cfkIBEREZGdKpVJwbCwMJP3USq1/6ucnZ3RpUsXo/f/+uuv8emnn2qtmzlzJmbOnGlyLER5qdQaLDkUhbl7ruc7b6CxPt1+GR1rlYO3q6NE0Rlw/wywbjiQ8sC47VMfi9uP+QdwKGO9uIiIrMkrUFwaDhMfJ937L0EYfUQcfiyVwPwLljk7mFBt+H44kBIDXNsuLgDg5AkEthIThIFtsGCP4ZusZ+4kYvTyU6hbyQNTOoaga6g/5HImB4mIiIjsSalMCha1RYsW4a233tJaN2XKFMyZM8dGEVFJER6dgHe3XMDVhymStJeQpsLak3cwuWPBvV7NFrEB+GMqkJ1h2n4x58T9+i0udBgbEVGx4FkZaDBYXAAg+YGYJIw+LA45fnLT/LaD2koT4+3D+usyk4Dr/4gLgK+FMhjsUBMnNLVxXFMbF4WqUOO/xOPF+8mYtCocNf3dMaVTMLrXqwAFk4NEREREdoFJQStbs2YNXn31Va11o0ePxrx582wUEZUESekqfPXPVaw5aVwhEWN4OCsxq3ttDGpaRZoG89Kogd2zgaMW/N1f2AhUaQE0Hy9ZWEREdsOjIlB/oLgAQMpD7TkJ464Z146TJ1C+njQxRRtICurwkKWjk+IcOinOAQCeCs4I19TAcU0oTmhqIUKohmwoce1RCqauPYvvd1/H5A7BeLFhRSgV8oIbJyIiIiKrYlLQinbv3o1Ro0ZBo/lvSGetWrUwePBg7Nmzx6S2vLy80KRJE6lDpGLG3EIihenTsCLe7REKP3cnydrMlZ4IbBoL3NxtWTuBbYE6fSUJiYjI7rmXB+r2FxcAePo4z5yEh4HYK4b3C2ipNeef2bIzgbsnTd7NTZaBMEUEwhQRAIBUwelZkrA2TmhqIyK2OqZvPI8f9lzHqx2C0a9xJTgpJYiXiIiIiEzGpKAVHT58GNnZ2Vrrrl69im7dupncVlhYGPbv3y9RZFQcWVpIxJBAHxd82qcu2oX4SdamltjrwNohQHykZe00Gw90+xxQGFktk4iopHErJ94Yybk5khoHRB8VE4TRR4BHF8X1Ug0dvn/G9KkeDHCVZaK94gLaKy4AANIFR4RrQnAiqTY2bwnFT7vrYGyHWhjcrIpp8x0SERERkcWYFCSyc1IWEsmhlMswKaw6pnQKtt6XsOs7gU3jgMxk89uQOwA9vgGavCxZWEREJYKrLxDaW1wAIC1eTBKWrytN+4bmE5RAGVkW2iouoa3iEgAgI9MBZ3eEYMXueqjUoAs6dukOV1c3qxybiIiIiLQxKUhkx6QuJAIATQO9MKdfPdTwd5esTS2CABz+HtjzMQALJjx09QMGrRSrXBIRUcFcvIHaPaVrz4j5BKXgLFOhleIyWmkuA2fXI+usEvc968O3Tkc4BYcBlZsBji5FEgsRERFRacOkoJE6dOgAwcSKDrNnz8bs2bOtExCVaNYuJCK3VuXHrDTgjynAxU2WtVOhATB4NVDWCkVPiIioYNlZZs0nKAVHZKNS0hng6Bng6LcQ5A6QVW4KBLYBgtqIBaccXW0SGxEREVFJw6QgkR3JKSTy0Z+XEfe0mBQSyZF4F1g3DHgYYVk7dQcAvX9kzxAiIlt5cBZQpdk6CgCATKMC7hwTl0PfAHIlULGxmCAMagtU7wzIdG50qVXiFBZx14GsVDGJ6FsDqPE856YlIiIiyoNJQSI7USwLieSIPgqsHwGkxVnQiAzo8iHQ5nX9L3hERFR04iPF5Jsmu/Bti5omG7h3UlwiNgJvXPzvueQYIHwZcGqp+HkkVwCQA9AAGjXg4gs0Gws0GQ14VLDVKyAiIiKyG0wKEtmYNQqJOChkmNjeyoVEcpxeBvz9JqBRmd+GkwfQfylQo6t0cRERkXkaDgNCXxSHEEcfEYuO3Dtt2XneGoLa/HcTKeoQsHYwoMoABLW4TqMGoP5v+7Q44OA3wLH5wND1QNV2RR4yERERkT1hUpDIhsKjEzBr8wVceyRdIZFmQV74rK8VC4nkUKuAHW8Dp5da1o5PMDBkLeBXQ5q4iIjIco6uQPWO4gIAqnTg3ikxQXj7iPizWrppLsyxMS4QzeJSEZRyBljZBxA04lIQQS2+lpV9gBFbmRgkIiKiUo1JQSIbyCkksvrEHcnaLJJCIjlS44ANI8UeJJYIfg7ovwQoU1aSsIiIyEocygBV24sLIPbIu3/6WZLwsJgkzM4o0pDmR5VH5rdbsN95BpyggaywhGCOnO3WDgGmnOZQYiIiIiq1mBQkKkLFupBIjpgIsaBI0l3L2mnzGtD5w2dzPhERUbHi4CwW+ghqKz7OzgTuh4u9CKMPA3dOANnpVjt8jOCNaMEfbyg3wUGTCZnMxOk3BI1YTCV8OdBxplViJCIiIrJ3TAoSFbG1J+9IlhAsskIiOS5tAba+allVSqUz0Hs+UH+gdHEREZFtKZ2AwNbigjeB7CyxivHtQ2Kv8jvHJa1ofEJTC0qoMVyxCwpTE4I5BI04BUb7GaxKTERERKUSk4JERUgmk+HTPnXRbe4hZGWbX1SkSAuJAIBGA+z7DDj0jWXteFQChqwGKjaSJi4iIrJPSkcgoIW4YIY4D+2Dc0D0YWTfOgRN9DE4qs1PEp7Q1EYn+Vn4yiyckzc1FvjnHSAjCWj7P8A/1LL2iIiIiIoRJgWJilg1PzdM6RiM73ZdN2v/IiskkiMjGdg8Abi+w7J2qrQABq0E3P2liYuIiIoPhQNQpRlQpRmUbd8A1NnIuBuO84f+RtatQ2iguQwPmfHDjY9rQtFNfgrZghxKc3sKAoBMAVz4HchIBC5sBGr2ANpPByo1Mb9NIiIiomKCSUEiG5gYVg3bzt1HZGyq0ft4lnHArO61MLBJERQSyfEkUpw/MPaqZe00Hgl0/0YcXkZERKRQwjmoBVoEtUCGSo0NJ29j7/49qJ52Di3lV9BcfhWeMsM9CR8LZREllIeLLAMCLPs8FADIMhL/W3Ftu7hU6wC0myHOmSgros9cIiIioiLGpCCRDTgpFZjTtx4G/3LcqO37NKyI93qGwtetCJNqN/cAv48Wh1SZS6YAXvgSaDaOX6qIiMggZwcFRrapjiEtqmLTmXv4eP9N3I9PRW3ZHbSQX8ldysrEG2nHNbUByJAmOEMGwbKDC2rD62/tF5fKzcU5B0O68nOMiIiIShwmBYlspEU1HwxqWhkbTt/Ld5siLyQCAIIAHF8I/PueOAm7ucp4A4N+A6q2ky42IiIqsRyVcgxtHoCBTSpj27kHWLDfHb/GBuFX9QuQQYOasntoKb+MSKEiACBSqGDZ0GGg8H6G904CawYB/vWAdv8DQl8E5EUwly8RERFREWBSkMiGZr5QG7uvPEZ8apbWegeFDJPCqmNyxyIqJJKXKg04vcyyhKB/XWDIGsArULq4iIioVFAq5OjfpDL6NKqEvy/EYP7em7j2KAVXhQBcVQfkbrdX0whxgrvlxUaM8eiC2HveJxho+wZQfzArFhMREVGxJ7d1AESlmZerI97rUVtrXbMgL/w9rR2md61Z9AlBAHB0BYauBZw8zdu/dm9gzE4mBImIyCIKuQy9GlTEjtfaYdGIJqhbyUPr+WwosVr9HNRCEV7OPrkJbJsMzGsEnPgFUBlfHIWIiIjI3jApSGRjfRtVQuvqPvAs44Av+9fD+gmtEFJUlYXz4xsCDFgKIwZWaev4rjhk2MnNKmEREVHpI5fL8Hyd8vhzSlssG90MjQPK5j63Orsz0uEItWDa55Vg4VSESLoL7HgT+KE+cPgHICPZwgaJiIiIih6TgkQmEAQBOy7EIDUzW7I2ZTIZvh7YAHumh2Fws4CiqyxcmJDngOc+Mm5bRzdxuHDYW5yInYiIrEImk6FjzXLY9EprrBnXAlW8y+AxvDBONQMayI1ODKoFmXQfVamPgd0fAj/UBfbNAdLiJWqYiIiIyPqYFCQy0t34NLy87BReWX0GP+y+LmnblcqWKdrKwsZqPQ2oN7DgbbyqAuN2A7V6FE1MRERUqslkMrQO9sV7PUIBAMc1oRihmol0OBU6lFgtyCCY2gveGBlJwIEvge/rAjvfBZJjpD8GERERkcSYFCQqhEqtwU/7I/Hc9wdw4HosAODXI7dx8X6SjSMrAjIZ0PtHoEIDw89X6wCM3wuUq234eSIiIivpVKscvF0dAYiJwU6Z3+JHdR/ECeIUHNmCHCpBgexnicI4wQM/qvtihmoiTmlqWCcoVSpwbD4wtz7w1xtAwm3rHIeIiIhIAqw+TFSA8OgEzNp8AdceaVc2VGsEvLvlAja/2gYKexnuay0OZcShwb90FIdJ5Wj5KvDcJ4CCpxEiIip6Dgo5XmoZiPl7b0AjAI/hhR+yB2B+dh90lJ9DddkDuMoykCo4I1KoiH2ahsh+dum7NasdWsiv4MtyuxCUeFz64NRZwOlfgfAVYo/7tm8A5WpJfxwiIiIiC/DbPJEBSekqfPXPVaw+cSffbc7fS8Kq49EY1Tqo6AKzFc/KwOCVwPKeYu/Bnj8AjYbbOioiIirlhrcIwNJDt5CuUkPzrHhINpTYpWmKXQXsJ5cBFx3qosyYKUDKZeDQt8DVv6QPUFADEeuAiPVA7Z5Au+lAxUbSH4eIiIjIDBw+TJSHIAj48/wDdP72QIEJwRxf77yGh0kZRRCZHQhoCfRZCIzewYQgERHZBX8PZywZ1QxymQzGdtyXywC5TIalo5rB38MZqNQYGLIaePU4Lvl2yx1uLC0BuPIn8EsHYGU/IPqoFY5BREREZBomBYmeufMkDaOWncLUtWcR9zTTqH2eZmbjoz8vWTkyO1J/EFC5qa2jICIiytWqug9Wjm2BMo6KQhODchlQxlGBVeNaoGU1H63nfr/rjh73RqJj1rdYnd0ZmYKVBtRE7gGWvQD82g24sRsQBOsch4iIiKgQTApSqadSa7Bw/0089/0BHHxWSMQUOy4+xO7Lj6wQGRERERmjVXUf7J3eAVM7heQWH1HIZVDKZblz//q4OmJqpxDsnd5BLyF44tYTzNwcAQC4K/jj3eyxaJ/5AxZnd0ea4GSdoO8cA1b3B34JAy5vAzQa6xyHiIiIKB+cU5BKtfDoeMzafFGvkIipPvzjElpV94Grkx29pW4dAFx8gPJ1bR0JERGR1fl7OOON52pgSqdg7Lv6GJGxqUjNzIarkxLV/VzRsVY5OCj074ffjkvFxFXhUKm1e+w9gjc+y34JC7N742XlTrys+BeeslTpA485D2wYCfjWFAuS1BsAKBykPw4RERGRDjvKYBAVnaQ0Fb7ceRVrjJg30Bj3E9OxYN9NvNXNDioLCgJw8hfgn5mAZyVg/H7A1afQ3YiIiEoCB4UcXeuUN2rbpDQVxqw4hcQ0Vb7bJMAD32cPxOLsHhih2I2pLjvhokqQKtz/xF0Dtk4C9s8Bwt4GGr0k/TGIiIiI8uDwYSpVBEHAH+cfoPN3ByRLCAJA30aVMKZtVcnaM1t2JvDHFGDHW2LFw8Q7wMZRgDr/LztERESlkUqtwSurw3Er1rjef0/hgp/UvdE45TtsKf8aBI9K1gks8Q7w6LJ12iYiIiLKgz0FqdS48yQN7227aNa8gfkJ8nHBp33qoW2Ir2Rtmi3lEbD+JeDeSe31tw8BO2cB3b+2TVxERER26KM/L+Fo5BOT98uAE9643QIbArtgcetIuJ38EYiPlC4whSPQeop07RERERHlgz0FqcSztJCIIQ4KGaZ2CsY/r7e3j4Tg/XDglw76CcEcJ38BwlcUaUhERET2rHvdCvBwNv/++LHoFPQ4FISbg/YBA34F/CWaw7fhMMCjojRtERERERWASUEq0cKj49Fz3mF89c81ZGZLU9WvWZAX/p7WDtO71oSzg0KSNi1yfj3w6wtAyoOCt9s+HbhzomhiIiIisnOtg32xdXIbBPm4mN1G9JM09Pv5OI44hwGTDgND1wOVm5kflEwOtHnd/P2JiIiITMCkIJVISWkqzNpyAf1/OmZxZeEcnmUc8GX/elg/oRVC/N0ladMiGjXw73vAlgmAOtOI7VXi8OKke9aPjYiIqBio5ueGLa+2QfOq3ma3kZyRjZG/nsSak3eBmt2AsbuAUX8CVcNMb6zuAMDbDuYoJiIiolKBSUEqUaxZSGTP9DAMbhYAuVwmWbtmS08AVg8Ejv5o2n6pj4F1wwFVunXiIiIiKma8XB2xamwLDGhS2ew21BoBs7ZcwKd/XYZaAFC1PTDqD2DcHqBmd+Mbavc/s2MgIiIiMhWTglRi3HmShlHLTmHa2rOIe2pEzzkjBPm4YNXYFvh+cEP4ujlJ0qbFYq8BizsDkXvM2z/mHPDHVEAQJA2LiIiouHJUyvH1gPp4q1tNi9pZcjgKE1eGIzUzW1xRuSkwdC0w6YjYC1BWwKV3rZ5AudoWHZ+IiIjIFEwKUrFXKgqJ5Lj2j5gQtKTKodwBCGoLyOygxyMREZGdkMlkeLVDMH5+qTGcHcy/RN595REG/HwMDxLz9MovXxcYsBSYchpoPFL8LNbVbrrZx9ST/ACI3McbgERERFQg80uuERUxlVqDvVcfIzL2KdIy1XBxEot8bD1zH9cfP5XsOM2CvDCnbz37mDcwhyAAh78D9nwCwIILfFc/YNBKILCVZKERERGVJN3qVsCGsmUwbsVpPE4xb+TBlZhk9FlwBEtGNUX9ymX/e8KnOtD7RyDsbXEKkPAVQHY6UL0TUKmxNC8AAI7MBU78DFRqIiYba7wAyNkXgIiIiLQxKUh271FyBlafuINVx6MRn5oFhVwGGcT5e6S8/+1ZxgGzutfCwCZV7GPewBxZacC2ycClzZa1U6EBMGQN4Gn+nElERESlQf3KZbFtShuMXX4al2OSzWrjcUomBi06hu8HNcQL9SpoP+lZGXjhS6DdDOD4QiCkqwRRP/M0Vkw2AsD9cGDdMKBcKND2f0CdvoCCl/9EREQk4i1DsmvHIp+g0zf7MX/vDcSnZgEQk4HZEicE7a6QSI7Eu8Cvz1ueEKw7ABj9DxOCRERERqrgWQYbJ7VCl9r+ZreRodLgldVnsGDfTQiGhvK6+QFdPpS2B//xhWLvw7weXwY2jwPmNwXClwPZ0sy9TERERMUbk4Jkt45FPsGIpSeQrlJDY6UpceyykEiO20eAXzoADyMsaEQGdPkI6L8EcHSRKjIiIqJSwdVJiUUjmmB8u6oWtfP1zmuYsTECWdkaiSLLR3oicGpJ/s8nRAF/vgbMbQgcWwhkpVo3HiIiIrJrTAqSXXqUnIFxK05BIwhWSQjabSGRHKeWAr/1BtLizG/DyRMYtgFo+zqLihAREZlJIZfh3R6h+LxfPSgtGE2w6cw9vLT0BBKejXywilOLgUwjhjunPAB2zgR+qAcc/EZMJhIREVGpw6Qg2aXVJ+5YrYdgsyAv/D2tHaZ3rQlnB4X0B7BEdhbw1xvA9v8Bmmzz2/EJBsbvAWpIOEcRERFRKTa0eQBWjGkOD2fz5+Q7GRWPPguPIDJWugJpubJSxd5/pkh7Auz9REwO7vkYSLXgZiQREREVO0wKkt1RqTVYdTxa8oSgZxkHfNm/HtZPaGVflYVzPI0FfnsROP2rZe2EdAXG7QF8Q6SJi4iIiAAAbYJ9sfnVNgj0MX9Kjugnaei74AiO3pQ4ARe+HEiPN2/fzGTg0LfA93WBHe8ASfclDY2IiIjsE5OCZHf2Xn2cW1REKnZbSCRHzHlgcUfgzlHL2mnzOjB0HVCmrBRRERERkY7gcm7Y+mobNK/qbXYbyRnZGPnrSaw7eUeaoLIzgaM/StBOOnDiJ2BuA+CPqcCTSMvbJCIiIrvFpCDZncjYp1BIlLiz60IiOS5uApY+DyTdNb8NpTPQfynw3EeA3M6GRBMREZUwXq6OWDm2Ofo3rmx2G9kaAe9svoDPtl+G2tLhEefWACkxlrWRl0YFnPlNrFb8+1jg0WXp2iYiIiK7waQg2Z20TDWkSAk2DfSy30IiAKDRiPP3/D5GvDNvLo9KwJh/gHoDpIuNiIiICuSkVOCbgfXxVreaFrWz+FAUJq4MR2qmBXMJP7kJSHL1pEPQABd/B35qBawdBtwLl/4YREREZDNMCpLdcXFSwNLpBOUyoHNtf/srJJIjIxlYN1Scv8cSVVoCE/YDFRtJEhYREREZTyaT4dUOwfhpeGM4O5h/Wb37yiMM/PkYYpLMvEn4/GfAlFNAw5cAufmFUAp0bTuwpJM4/3HUQUCwQjU4IiIiKlJMCpLdqe7nZvEwGo0AVPdzlSgiiT2JBJZ0Aa7/Y1k7jUcBo/4E3MpJExcRERGZ5YV6FbB+Qiv4uZs/VcnlmGS8OP8ILtxLMq8B3xCgzwJg2lmg2XhAYaVpU27tB1b0ApZ2Ba79w+QgERFRMcakINmdTrXKwdvV0aI2fFwd0bGWHSbLbu4WC4rEXTO/DbkS6P4N0GsuoLTs/4mIiIik0aBKWWyb3Aa1K3iY3UZiugoqjcayQMoGAD2+AV6/ALR5DXB0s6y9/Nw7CawdDPzcDri4GdCorXMcIiIishomBcnuOCjkeKllIMytNSKXAS+1DISDwo7+vAVBrAq4eiCQYWYPAAAo4w2M2Ao0Hw/I7LCKMhERUSlWsWwZ/D6pFTqbeWPy24EN0DjAS5pg3P2B5z4G3rgIdJgFlJGoXV2PLgC/jwYWNAfOrgKys6xzHCIiIpKcHWVNiP4zvEUAyjgoTE4MymVAGUcFhrUIsE5g5lClA1smAv++J07YbS7/uuL8gVXbSRYaERERScvVSYlfRjbFuLZVTdrvjS410KtBRekDKuMFdHgbeP0i0PVTwM1f+mMAYrGTbZOBeY2AE7+I1z9ERERk15gUJLvk7+GMJaOaQS6TGZ0YlMsAuUyGpaOawd/D2boBGiv5AbCsOxCx3rJ2Ql8Exv4LeAVKExcRERFZjUIuw3s9QzGnbz0ojLiQ6dOwIqZ1DrZuUE5uQOupwGsRQI/vxGHG1pB8D9jxJvBDPeDw92JxNSIiIrJLTAqS3WpV3Qcrx7ZAGcfCewzm9BBcNa4FWlbzKZoAjbHnE+DBGcva6PgeMHAF4GinhVOIiIjIoGEtArBidHO4O+dfEbhJoBe+6F8fsqKaFsTBGWg2Fph6Bui7CPCtaZ3jpMYCu2cDP9QF9n4GpMVb5zhERERkNiYFya61qu6DvdM7YGqnkNziIwq5DEq5LPfOu4+rI6Z2CsHe6R3sKyEIAC98AfiEmLevoxswZA0Q9ibnDyQiIiqm2ob4YsurbRDg7aL3XBXvMvhlRBM4OyiKPjCFA9BgCPDqcWDQb0CFBtY5TkYScPArsWIxKxUTERHZlfxvWxLZCX8PZ7zxXA1M6RSMfVcfIzI2FamZ2XB1UqK6nys61ipnX0VF8nL2BIauBRZ3BjJNKDDiVVXcr1xt68VGRERERSK4nBu2Tm6DSSvDcfK22GPO3UmJX0c1g4+bk22Dk8vFaUpq9wZu7gEOfQPcOSb9cZqN401OIiIiO8OkIBUbDgo5utYpb+swTOcbAgxYKlYehhF3yKt1BAb8Crh4Wz00IiIiKhrero5YOa45Zm6+gG3nHmDB8MYI8Xe3dVj/kcmAkC7iEn0UOPQtcHO3NG27VwAaDpOmLSIiIpKMnXavIiphQp4DuswufLuWk4HhvzMhSEREVAI5KRX4dmADbH21DdrX8LN1OPkLbA28tAmYsF/sQQgLe/i1ngoobdwjkoiIiPQwKUhUVNq8BtQbaPg5hRPQ5yeg2xxAwQ68REREJZVMJkO9yp62DsM4FRsBg1eK8w7WHwLIzJj7sIw30ORlyUMjIiIiyzEpSFRUZDKg949AhYba693KA6P/5rAaIiIisk/lagH9FgHTzgBNxwAKR+P3bfkq4OhqvdiIiIjIbEwKEhUlhzJiRWHXcuLjSk3FoTmVm9o0LCIiIiq+0rKycfB6rPUP5BUE9PweeC0CaDUFcCgk2efoDjQfb/24iIiIyCxMChIVNc9KwOBVQOORwMvbAY8Kto6IiIiIiimNRsAb689h5K8n8dP+SAiCEUXNLOVRAXj+M+CNi0DY24BzPsOhm48DypSV5piCAKizpWmLiIiIADApSGQbAS3EocQOzraOhIiIiIqxr3Zew85LjwAAX/5zFW/9HoGsbE3RHNzFG+g4C3j9olhQzTVP8RSls1hATSrRR4AfGwGnlgKqDOnaJSIiKsWYFCQiIiIiKoY2nL6Lnw9Eaq3bGH4PI5aeQEJqVtEF4uwBtH0DeP0C8MLXgEdloPEowE3CCsuHvgUS7wDb/wfMbQAc/RHIfCpd+0RERKUQk4JEhcnOBO6H2zoKIiIiolzHIp9g1uYLBp87ERWPvguP4FZsESfNHMoALSYA084Cnd6Trt374UDk3v8eP30I/Pse8ENdYP+XQFq8dMciIiIqRZgUJCpIykNgeU9geS/g4UVbR0NERESEqLhUTFoVjmxN/vMH3n6Shr4Lj+JoZFwRRvaM0lHsPSiVQ98ZXp+eAOyfA/xQD9j1AfD0sXTHJCIiKgWYFCTKz/1w4JeOwL2TgCoVWDcUSH1i66iIiIioFEtMy8KY5aeQlK4qdNukdBVGLj2J9afuFEFkVvL4CnD1r4K3yXoKHJkrJge3zxCHGRMREVGhmBQkMuT8euDXF4CUB/+tS7wDbBwFqAu/CCciIiKSWla2BpNWhSMqLtXofbI1At7edAGf/30FmgJ6Ftqt/HoJGpKdAZxaDMxrBGx9FYi7Yb24iIiISgAmBYny0qjFOWq2TADUmfrP3z4E7JxV9HERERFRqffBtos4fsu8+fMWHbyFSavCkZaVLXFUVhR/C7j4u+n7abKBc6uB+c2ADaOAmAjpYyMiIioBmBQkypGeAKweIFazK8jJX4DwFUUTExEREdEz7UL84KQ0//L938uPMPDnY3iYlCFhVFZ0ZC4gaCxoQAAubwUWtQNWDwLunJAqMiIiohKBSUEiAIi9BizupF3ZriDbp/PCkoiIiIpUj/oVsH5iK/i6OZndxqUHyXhxwWFcvJ8kYWRWkPwAOLdGuvZu7AR+7SoWkIvcCwjFcCg1ERGRxJgUJLr2D7C4szhExVgaFbD+JSDpnvXiIiIiItLRsEpZbJvSBrXKu5vdxqPkTAz8+Rh2XnooYWQSO7YAUGdJ3+7tQ8DKvuLN4KvbAY0lPRGJiIiKNyYFqfQSBODgN8DaIUBWiun7pz4G1g0HVOnSx0ZERESUj0ply+D3V1qjc61yZreRrlJj0qpw/HwgEoI99ppr+wbQbjrg5GGd9h+cAdYNA35uA0RsBNTFaK5FIiIiiTApSKVTVirw+2hg7ycALLkQFoCMZKmiIiIiIjKKm5MSv4xsirFtq5rdhiAAX+y4irc3RSAr2856zLn6Ap0/AN64CHR6H3Dxsc5xHl8GNo8D5jcFwpcD2QYKzREREZVQTApS6ZN4B/j1eeDSFsvaqTcQGLMTcPeXJi4iIiIiEyjkMrzfMxSf9qkLhVxmdjsbTt/DyF9PIDHNCsN1LeXsCbSfAbx+Eej2BeBe0TrHSYgC/nwNmNsQOLZQvIFMRERUwjEpSKXL7SPALx2BhxcsaEQGPPcx0G8x4FBGstCIiIiIzPFSy0AsH90M7s5Ks9s4fisefRcexa3YpxJGJiFHF6DlK8Br54Be8wAv83tIFijlAbBzJvBDPeDg10B6onWOQ0REZAeYFKTS49RS4LfeQFqc+W04eQLDNwJtXgNk5t+RJyIiIpJSuxA/bHm1Nap4m3/DMiouFX0XHsWxyCcSRiYxpRPQZBQw5TTQfylQLtQ6x0l7Auz9VEwO7v4ISLXg+pGIiMhOMSlIJV92FvDn68D2/wEaCyaR9gkBxu8BQp6TLDQiIiIiqQSXc8fWV9ugWZCX2W0kpaswYukJbDh1V8LIrEChBOoNACYdAYasBSo1sc5xMpOBw98B39cFdrwDJN23znGIiIhsgElBKtmexgK/vQiEL7OsnZCuYkLQN0SauIiIiIiswMfNCavGtUDfRpXMbiNbI+CtTRH4fMcVaDR2WJk4L7kcqNUdGLcHGLkNCGpnneNkpwMnfgLmNgD+mAo8ibTOcYiIiIoQk4JUcsWcBxZ3BO4ctaydtm8AQ9eJE10TERER2TknpQLfDWqAGV1rWNTOogO38MrqcKRlWTDSoqjIZEC1DsDLfwFjdwE1ulnnOBoVcOY3sVrx72PFESlERETFFJOCVDJd3AQsfR5IsmDoi7KMOFdNl9mAXCFZaERERETWJpPJMKVTCOYPawQnpfmX/DsvPcKgRcfwMClDwuisrEpzYNh6YNJhoE4/AFaYB1rQAOkJgNJR+raJiIiKCJOCVLJo1OJk0L+PEYd5mMujEjDmH3GuGiIiIqJiqmf9ilg3oSV83ZzMbuPi/WS8uOAwLt5PkjCyIlC+HjBwmViUpOFLgNz86swGtZ8hbXtERERFjElBKjkykoC1Q8XJoC0R0AqYsB+o2FCKqIiIiIhsqlGAF7ZObo1a5d3NbuNRciYG/nwM/156KGFkRcQ3GOizAJh2Dmg+AVA6W95mQCsgsLXl7RAREdkQk4JUMsTdBJZ0AW7stKydJi8DI/8A3MpJEhYRERGRPajs5YLfX2mNTrXMv8ZJV6kxcVU4fjkYCUGw8wIkhpStAnT/Gnj9AtDmdcDR/CQp2rGXIBERFX9MClLxd2M3sLgTEHfd/DbkSqDHt0CvuZwbhoiIiEokNyclFo9sijFtqprdhiAAc/6+inc2XUBWtkbC6IqQWznguY+ANy4AHd8FyniZtn+FBkBwZ+vERkREVISYFKTiSxCAI/OANQOBTAvmuHHxAUZuA5qNky42IiIiIjukkMvwQa9QfNqnLhRy8wtwrD99F6N+PYnEtGJcfbeMFxD2FvD6RaDrZ4BbeeP2azddrHZMRERUzEk82y6RFalVwPWdYo/AjCQgci/wMMKyNv3rAUNWA16B0sRIREREVAy81DIQAd4umLz6DFIys81q49itJ+i38CiWvtwMVX1dJY6wCDm5Aa2niDeIz68BDv8AJEYb3ta3BlCrV5GGR0REZC1MCpL9S44BwpcBp5YCaXGATAEIasvbDe0D9FkIOBbji1giIiIiM7Wv4YfNr7bGmBWncDc+3aw27iemIyldJXFkNuLgDDQdAzQaCVzcJBavi72qvU3b/wFyiQZbqTKAYz8CTcYArj7aN8CzUsVrVN8aQI3nAYWDNMckIiLKg0lBsm9Rh4C1g8WLppxEoBQJwU7viRNEc+gHERERlWIh/u7Y+mobTFwZjtPRCSbv/92ghmhYpaz0gdmSQgk0GAzUGwhc2w4c/AaIOQeUDQDqDZDuOOfXAHs/Fdv3rwvE3wLS4wG5AuIsTxpAowZcfIFmY4EmowGPCtIdn4iISj3OKUj2K+oQsLIPoEqXJhEIiFXmhqwF2r/JhCARERERAB83J6wa1wJ9G1Uyab8ZXWugR/0SnKSSy4HavYAJ+4GXNgPdvpSux546WxymDADZGcD902JCEBATgRqV+C8gjpQ5+A0wv4l4fUxERCQRJgXJPiXHiD0EBY24SMG7GjBuN1CruzTtEREREZUQzg4KfDeoAf73XA2jtu/XuBImdwy2clR2QiYTqw1LeQ15cVP+8xYaIqjFG+Ur+zAxSEREkmFSkOxT+LJnQ4YlSghW7wSM3wuUqyVNe0REREQljEwmw7TOIfhxaCM4KfP/mtAsyAuf96sHGUddmEejAQ58afp+OTfL1w4Rb6ATERFZiElBsj9qlVhURKohw62mAMM2AmW8pGmPiIiIqATr1aAi1k1oCV83R73nArxdsGhEUzgpFTaIrIS4th2IjzRvX0EDqNKA8OWShkRERKUTk4Jkf67vFOdOsZRcCfT5GXj+M3HCaCIiIiIySqMAL2yd3AY1/d1z17k7K/Hry83g7aqfLCQjCQJw4GsL29AAp5eKN9KJiIgswKQg2Z+468+qrlmoyWig4VDL2yEiIiIqhSp7ueD3V1qhQ00/KOQy/DS8CYLLudk6rOItci/w8Lzl7aTG4v/s3Wd0VGXb9vFj0kMqJYTee+9VOiqKNEGqgliQYr2xN+xYUVEQUOlIkaqA2ACBUKT3DqGGGiAhPZl5PuTJyBAgM5M9qf/fWllv9s4+r33E9T7hzpmr6PAfmR8HAJCvMX0KOU9ijFL71ZlYPuzmIfkEGZUIAAAgXwrw8dQPAxtpx6mralSuUHbHyf3WfmHMOCb31D+kq7Mx4wEA8iVmCiLn8fKTlMkDRiwWyZu/ZAMAAGSWh7sbDUEjnNggnQgzbryE68aNBQDIl2gKIucpUkUyZ/KQEUtK6jgAAABATpAQJQWVNmYsS4p0fp8xYwEA8i2agsh5qtwrFSiSuTH8QqTK9xiTBwAAAIaKSUjWtpNXsjtG1qpyr/TsdqnJEGPGO7RcWvNZ6goZAACcQFMQOY+7p9T48dS9UpxhcpMaPZ46DgAAAHKUFLNFz83ZoT4TN2jellPZHSdruXtK936U+T+Ap1n5gfTn2zQGAQBOoSmInKnhYMnTJ7XB5wiTm+RZQGr4qEtiAQAAIHM+WXFAf+0/r6QUi16ev0sf/3ZAZnM+ampl9g/gN1s/Vlr6Qua33wEA5Ds0BZEzBRaX+s1NbfLZ2xhMe7b/3NR6AAAA5Chz/j2pSWuO2dyb8M9RDZ+1TXGJ+aip5ewfwG9n6xRp4RApJcmY8QAA+QJNQeRc5VtJjyxOnfmX0V9S02YIDlwilbsrS+IBAADAfuuPXNKbi/fc8msr9p5T74kbdD4qPotTZRNn/gCekT3zpbkPS0lxxowHAMjzaAoiZyvfSnp6i9T6pf/2XjG5S26e/zUK/UKk1i+nPkdDEAAAIMc5evG6hs7cquQ7LBPefeaaun0bpj1nrmVhsmzkyB/A7XVohTTrISkh2pjxAAB5mkd2BwAyFFhcavea1PpF6fAf0qVDUsJ1ydtfKlIl9ZRhDhUBAADIka7EJOqxqZsVFZ+c4bPnouLVe+IGfd23vu6uEZoF6bJZ2h/At06VNv8gxV76r0FocXI5dfhaaXo3acB8qUAhw6ICAPIemoLIPdw9pWqdJXXO7iQAAACwQ0Jyip6auVUnLsfaXRObmKIhM7bo9fuq64lW5WUymVyYMAe43R/Ar56U9ixwrjl4Zqs0tbP0yCIpoJjxmQEAeQJNQQAAAACGs1gsemPRHv17PNKJWunD5ft17NJ1vdetljzd88GuR7f6A3jdPtKch6VkJ/YJvLBPmtwpdc/tgmUNiwkAyDvywb+uAAAAALKayWRS3VJBcndzfqbf7H9PadDkf3UtNp+eqlupY+psP+9A5+qvHJem3CddPGRsLgBAnkBTEAAAAIBLPNK8nCY/2lgB3s4vUFp/9LJ6jA9T+KUYA5PlImWbS4N+lQoUdq4+6kxqYzBip7G5AAC5Hk1BAAAAAC7TpkqIFgxvoVIFfZ0e49ilGHUfH6ZNxy4bmCwXKVFPGvybFFDCufrYS9LULtLJjYbGAgDkbjQFAQAAALhUldAALR7RUg3LFnR6jKuxSXr4x036ecspA5PlIiFVpcdWSAXLO1efcE2a0UM68rexuQAAuRZNQQAAAAAuV8TfW7OeaKpu9Zyc7SYpKcWil+bv0icrDshsthiYLpcoWDa1MRhS3bn6pFhpdl9p3y/G5gIA5Eo0BQEAAABkCR9Pd33Vp55e6FglU+N8t/qohs/aprjEFIOS5SIBxaTBy6USDZyrT0mUfh4k7fjJ2FwAgFyHpiAAAACALGMymfRcx8oa26++vDyc/3Vkxd5z6j1xg85HxRuYLpcoUEga9ItU9i7n6i1mafEwadMkY3MBAHIVmoIAAAAAslzXuiU0Z0gzFfH3cnqM3Weuqfu4MO09e83AZLmEd4D08Hyp8r3Oj3FgqWTOh7MtAQCSaAoCAAAAyCYNyhTUouEtVTU0wOkxIq7F66EJG/TnvvMGJsslPH2lvrOkWj0dry3VWOr7k+TmbnwuAECuQFMQAAAAQLYpXaiA5g9rrjZVQpweIzYxRUNmbNH3a47JYslnB5C4e0oPfi81GGR/TWgtacDPkre/63IBAHI8moIAAAAAslWAj6d+HNRIj7Yo5/QYFov04fL9en3RHiWlmI0Llxu4uUtdvpZaPJPxs4UqSo8sknwLuj4XACBHoykIAAAAINt5uLvpna419V63mnIzOT/O7H9P6tEp/+pabJJx4XIDk0m6+32p3Zu3fyawlDRwieRfNOtyAQByLJqCAAAAAHKMgc3LafKjjRXg7eH0GGFHLqvHd2EKvxRjYLJcwGSS2rwkdfok/df8QlIbgsGlsz4XACBHoikIAAAAIEdpW7WoFgxvoVIFfZ0e49jFGHUfH6ZNxy4bmCyXaDZU6jZeMv3/r3s+QalLhotUyt5cAIAchaYgAAAAgBynSmiAFo9oqQZlgp0e42pskh7+cZPmbz1tXLDcov4A6aGpkk+wNGC+VKx2dicCAOQwNAUBAAAA5EhF/L3105PN1LVuCafHSEqx6MWfd+rTFQdkNuezk4lrdJOe3yWVbpLdSQAAORBNQQAAAAA5lo+nu77uW08vdKySqXHGrz6qET9tU1xiikHJcgmfoOxOAADIoWgKAgAAAMjRTCaTnutYWWP71ZeXh/O/wvy255z6TNqgC1HxBqYDACB3oikIAAAAIFfoWreEZj/ZTEX8vZwe49D5aJ2PSjAwFQAAuRNNQQAAAAC5RsOyBbVoeEtVCfV3qv6rPvVUuxRLap12brd0dGV2pwAAGICmIAAAAIBcpXShAlowrIXaVAlxqO6VTtXUqVZxF6XKBy4dkWb0kH7qI+37JbvTAAAyiaYgAAAAgFwnwMdTPw5qpEHNy9r1/EMNS2lomwouTpWHXT0lTe8mxVyUUhKlnwdJO37K7lQAgEygKQgAAAAgV/Jwd9O73Wrp3a415Wa6/XNNyxfShz1qy2S6w0O4vesXUhuCUaf/u2cxS4uHSZsmZV8uAECm0BQEAAAAkKsNalFOkx9tLH9vj3RfK1/ETxMebpipU4vztbgrqUuGI4/e+uu/vSSt+UyyWLI2FwAg0/iXEQAAAECu17ZqUS0Y1kIlg32t94J8U5cYF/Rz/rTifC3hujTrIen8njs/t/ID6c+3aQwCQC5DUxAAAABAnlC1WIAWj2ip+mWC5eFm0ncPN1CFEOdOKc73kuKlOf2k05vte379WGnp85I5xaWxAADGST+/HgAAAAByqZAAb81+spm2nbiiFhWLZHec3CklSZo/WDq+xrG6rVOlhGipx0TJ3dMl0QAAxsnSpmBsbKzOnz+vyMhIxcbGymKxqHXr1lkZAQAAAEAe5+PprhaVaAg67fAf0sHlztXuWZC67Lj3NMnTN+PnAQDZxuVNwX379mnSpEn6559/tGfPHpnNZuvXTCaTkpOTb1m3ePFi67MlS5ZU06ZNXR0VAAAAAFCts3Tfp9JvLztXf/j31L0I+82WvAOMzQYAMIzLmoIRERF66qmntGzZMkmSxcFNZydPnmytLVq0qM6cOSM3N7ZABAAAAJD1YhKSdfpKnKoWyydNrqZPpTb0loyQLOaMn79Z+FppWlfp4QVSgULG5wMAZJpLumyrVq1S3bp1tWzZMmsz0GQy2Xxk5LnnnpPFYpHFYtGFCxe0fLmT09cBAAAAIBNSzBY9O3u7Hhwfpr/3n8/uOFmnXn/poWmSm5P7A57dJk3tLEWfMzYXAMAQhjcFt23bpq5du+rSpUuSUpuBFotF7u7uqlatmsqXL2/XrMEOHTqoWLFi1gbikiVLjI4KAAAAABn6aPl+/X3ggmISU/Tk9C36cd1xh1dC5Vo1ukr950oeTu4PeGGfNLmTdOWEsbkAAJlmaFMwPj5ePXr0UExMjLUZWKZMGU2ZMkWRkZHau3evXnrpJbvH69q1q3W24N9//21kVAAAAADI0KxNJ/TjuuPWa7NFen/pPr2xeI+SUpxYVpsbVeogDVwseQc6V3/leGpj8OIhQ2MBADLH0Kbg2LFjderUKevsvrvuukvbtm3ToEGD5O/v7/B4bdu2tX5+4sQJXbhwwaioAAAAAHBH6w5f0ttL9t7yaz9tOqnHpm7WtbikLE6VTco0kx5dKhUo7Fx99FlpSifp7A5DYwEAnGdoU3DixInWGYKhoaFavHixChYs6PR4derUsbnev39/ZiMCAAAAQIaOXIjWsFlblWK+/TLhtYcv6cHxYTpxOSYLk2Wj4nWlwSukgBLO1cdelqZ1kU5sMDYXAMAphjUFDx06pOPHU6fVm0wmvfTSSypUKHOnTFWuXNk6niTr+AAAAADgKpExiXps6hZFxydn+OzRizHqPi5Mm8MjsyBZDhBSRXpshVSwvHP1CVHSjB7Skb+MzQUAcJhhTcEdO3ZIknXD3R49emR6TE9PT/n6/reh7bVr1zI9JgAAAADcTkJyip6asUUnI2PtrrkSm6QB32/Swm2nXZgsBylYNrUxWLSGc/XJcdJPfaV9HCYJANnJsKbgjfv9eXl5qVy5coaM6+fnZ200xsTkk2n5AAAAALKcxWLRawt2a3P4FYdrE1PM+t+8nfr894My32HJcZ4RUEx6dJlUsqFz9eYk6edHpR0/GRoLAGA/w5qC0dHR1s+dOVTkTuOmLR82clwAAAAAuFmpQgUyVf/tqiN6Zs52xSelGJQoBytQSBq4RCrXyrl6i1laPEzaNNHYXAAAuxjWFCxc+L9TqIxa5nvlyhUlJCTc8h0AAAAAYCSTyaT/3V1FX/WpJy93539VWrYrQn0mbdSF6HgD0+VQ3gHSgJ+lKp2cH+O3l6V/PpMs+WCGJQDkIIY1BYsWLWr9PCUlRYcPH870mJs2bZL03z6FpUqVyvSYAAAAAHAn3euX1E9PNlVhPy+nx9h56qq6fxum/RFRBibLoTx9pT4zpVo9nR9j1QfSn2/RGASALGRYU7B+/fqS/jsp+I8//sj0mAsXLrR+7unpqaZNm2Z6TAAAAADISKNyhbR4REtVLur8FkZnr8Wr13frtfLAeQOT5VDuntKD30sNH3V+jPXfSEufl8z5YOk1AOQAhjUFy5YtqypVqkhKndn3zTffKDk52enxTp8+rZkzZ8pkMslkMqlp06by8fExKm62i4+P18qVKzV+/Hh9+OGH+uyzzzR79mwdO3Ysu6MBAAAAkFS6UAEtGN5CrSoXcXqMmMQUPTFtiyavO25dAZVnublLD3wltXjW+TG2TpUWPimlJBmVCgBwG4Y1BSWpX79+slgsMplMOnz4sF577TWnxklKStKAAQMUHx9v/YfzySefNDKqQ/r162dtTqZ9OHu68sWLF/X000+rSJEi6tChg0aMGKE333xTL7/8svr376+KFSuqUaNGWrJkibHfBAAAAACHBfp4asqjjfVIs7JOj2G2SO8t3ae3luxRUorZwHQ5kMkk3f2e1P5N58fYs0CaM0BKijMuFwAgHUObgv/73/+sh4FYLBaNGTNGI0eOVGJiot1jnDt3Tvfcc4/Wrl1rXYpcvnx59e/f38iodvv11181Z84cQ8ZavXq1atSooXHjxikmJua2z23dulXdu3fXoEGDHPpvBwAAAMB4Hu5ueq9bTb3TpYbcTM6PM3PjST02dbOuxeXxWXAmk9T6Jem+T50f4/Dv0qyHpIRo43IBAGwY2hQMCAjQmDFjrLMFLRaLvvrqK1WvXl2ffvqpdu3aZXOasCQlJibq7NmzWrZsmYYPH66KFStqzZo11np3d3dNmjRJbm6GRrXLtWvXNGzYMEPGWrdune6//35dunTJ5n5wcLDq16+vcuXKyd3d3eZr06dPt86+BAAAAJB9TCaTHm1ZXj8Oaiw/L/eMC25j7eFL6vndep28HGtguhyq6VNS9+8kk5O/y4WvlaZ1lWIjjc0FAJBkcFNQkh555BG9/vrrNo3B48eP67XXXlP9+vX1wgsvWJ+1WCzy9fVV6dKl1bVrV02cOFFxcbZTxD/66CO1b9/e6Jh2eemll3TmzBlJkp+fn9PjXLlyRX369LH53sqWLavFixcrMjJS27Zt0/HjxxUeHq6nnnrKpnbhwoX68ssvnX43AAAAAOO0q1ZUC4a3UMlgX6fHOHLhurqPD9OW8HzQ7KrXX3pomuTm6Vz92W3S1M5S9DljcwEAjG8KStIHH3ygTz75RO7u7tY9+CwWi/XjRjfev7GR6ObmprFjx+qll15yRcQMrV69Wj/88IMkyc3NTaNGjXJ6rM8++0xnz561XpcvX17r169Xt27drEukJalUqVKaMGGCPvzwQ5v69957T1euXHH6/QAAAACMU61YoBaNaKF6pYOdHiMyJlH9v9+kxdvPGBcsp6rRVeo/V/JwspF6YZ+0cIixmQAArmkKSqmz7P755x81b97c2gi8+bCOmz+k1CZh48aNtXLlSj399NOuindHcXFxeuKJJ6y5n3nmGTVu3NipsS5evKhvvvnG5t7333+vEiVK3LbmtddeU+vWra3X165d0+eff+7U+wEAAAAYr2iAj+YMaaYH6hR3eozEFLOen7tDY/44KLM5j28ZVKmDNHCx5B3oeK1/qPQAq6cAwGgu3aivefPmWrduncLCwvT000+rVq1aktLPDrRYLCpVqpQee+wxLV++XJs2bVKrVq1cGe2O3nrrLR09elSSVKZMGX3wwQdOjzVnzhxdv37det26dWt16NDhjjUmkyndzMTJkyeztyAAAACQg/h4umts3/p6tn2lTI0zduURPTNnu+KTUgxKlkOVaSY9ulQqUNj+Gp9g6ZFFUuGKLosFAPmVR1a8pHnz5mrevLkkKTY2VhcuXFBkZKQSExNVqFAhhYSEqGDBglkRJUObN2/WV199Zb0eN26c/P39nR5vyZIlNtePP/64XXXt2rVT+fLldfz4cUmppzJv3LjR+t8RAAAAQPZzczPpf/dUVfkQP70yf7cSU8xOjbNsV4T2nrmmznWKyySTCni7q2KIv9pXKypP96w/dNFliteVBq+QpneTos/e+Vkvf+nhhVJozazJBgD5jGFNwfj4eF24cMF67e/vr0KFCqV7rkCBAipXrpzKlStn1KsNk5SUpMcff1wpKal/oXvooYf0wAMPOD3e9evXtWbNGpt799xzj121JpNJHTt21Pfff2+9t3TpUpqCAAAAQA7Uo34plS5YQENmbFVkTKJTY4RfjtW4VUfl7pa6tVKK2aJCfl56uFlZDWhaRqGBPkZGzj4hVaTH/r8xeOX4rZ9x95b6zZZKNczabACQjxj2J6dZs2apfPny1o+5c+caNXSWGT16tHbv3i1JCg4O1tixYzM13t69e5WUlGS9Ll++vIoVK2Z3fcuWLW2ud+zYkak8AAAAAFynUblCWjy8pSoVdX6lkZTaDEz5/z0GI2MS9e3Kw2r/+WptOHrZiJg5Q8GyqY3BojXSf83NQ+o9TSrfOv3XAACGMawpeOHCBZvThXv16mXU0Fli3759Nqf+fvLJJw418G5l//79Ntc1atziH7w7uPn5m8cDAAAAkLOUKVxAC4a1UKvKRQwb02yR4pJS9MiPm/JWYzCgmPToMqnkjbMBTVKPiVLV+7ItFgDkF4Y1Bd3c/hvKx8dHISEhRg3tcmazWY8//rgSE1On+bdq1UpPPvlkpsc9ePCgzXXp0qUdqr/5+RMnTig+Pj7TuQAAAAC4TpCvp6Y82lgPNytj2Jhmi2S2WPTE9M06H5WHficoUEgauEQq9/8HTT7wpVQ7d00wAYDcyrCmYOHC/50g5eXlZdSwWWLs2LHauHGjpNTskyZNkslkyvS4N+6xKEmlSpVyqD40NFQeHv9t+2g2m3X5ch76yyAAAACQR3m4u+n9brU0qksNuWX+VwtJ/z9jMDFFP206acyAOYV3gDTgZ6n3DKnR4OxOAwD5hmFNwWrVqlk/j4qKUkJCglFDu9Tx48f15ptvWq9fe+01m+8lM65fv25z7efn51C9yWSSr6/vHce8lYSEBEVFRSkqKkoxMTEOvRMAAACAMUwmkwa3LK8fBjWSn5e7IWOaLdLMjSeU5OQpxzmWp69Uo2t2pwCAfMWwpmDTpk3l7//fhrr//POPUUO71JAhQ6yNs2rVqun11183bOybG3g+Po6fFuZMU3D06NEKCgpSUFCQOnXq5PA7AQAAABinfbVQzR/WQiWDfTN+2A6XYxK16sCFjB8EAOAODGsKenp66uGHH7ZeT5o0yaihXebHH3/UX3/9JSn1r3iTJk0ydOnzzfv/OTO2t7e3zXVcXFyGNa+99pquXbuma9euacWKFQ6/EwAAAICxqhcP1KIRLVQsyPGJAjdzdzPp6EVWBAEAMsewpqAkvf322woMDJQkLVq0SD///LORwxsqIiJCL774ovX6iSeeUKtWrQx9x80zA9MOMnHEzcuw7Zlt6O3trcDAQAUGBjq8ZBkAAACAaxQN8FH3eiWU2S0GTZJiEpKNiJS3xUZKSRlPqgCA/MrQpmCxYsU0a9YseXh4yGKx6JFHHtGECROMfIVhRowYoatXr0pKzf3pp58a/o4bl1NL6WcO2uPmmYE3jwkAAAAg9wj09ZRbJk8esUjy8/bI8Ll8LSFamtlTmtlLio/K7jQAkCMZ2hSUpM6dO2v58uUKDQ1VYmKiRowYoXr16mncuHHat2+fLBaL0a902M8//6xFixZZr7/++msFBwcb/p6bG3iOHvphsVhoCgIAAAB5SMUQf6WYM/c7UYrZooohrAi6raQ4aXY/6ew26cQ6aXrX1FmDAAAbhv55qUKFCtbPk5NTp7NbLBbt2rVLzz77bOoLPTwUFBTkcHPLZDLp6NGjhuR86aWXrJ937txZvXv3NmTcmxUtWtTm+vTp0w7Vnz9/3vrfUZLc3NxUpEgRQ7IBAAAAyHrtqxVVIT8vRcY4vrVQmsJ+XmpXrWjGD+ZHKUnSz49K4Wv/u3d2uzTlPumRxVJg8exKBgA5jqFNwfDwcJlMJlksFplMJplMqdPiLRaLdYZgUlKSLl26pEuXLjk0dtpYRkhbNixJy5Ytc2rsEydOpKvbvn276tWrZ72uWrWqzddPnjzp0Dtufr5s2bJOnWAMAAAAIGfwdHfTw83K6tuVh+XMhEE3k/Rws7LydDd80VfuZ06RFj0lHbrFYYsXD0hTOkkDl0gFy2V5NADIiVzyL8nNzbK0BqGzH7lVtWrVbK737dvnUP3+/fvvOB4AAACA3GdA0zLy9XSXo1sLupkkXy939W9axjXBcjOLRVr6grRnwe2fuRIuTe4kXTiQZbEAICczvCmYNivQyI/cqmbNmvL09LReh4eHKyIiwu76sLAwm+sbZyECAAAAyJ1CA330w6DGcjOZ7G4MupkkN5NJPw5qrNBAVg/ZsFikP9+Stk3L+NnoiNSlxGe3uz4XAORwhi4fPn78uJHDucySJUuUlJTkUM3OnTv14osvWq9DQ0M1c+ZMm2cqVapkcx0QEKDWrVvr77//tt77888/NXDgwAzfZ7FY9Ndff9nc69Kli0OZAQAAAORMzSsW1ozHm+qJ6ZsVl5hyx6XEaTMEfxzUWM0qFM66kLnF2s+l9d/Y/3xcpDStq9R/rlS2hetyAUAOZ2hTsGzZskYO5zJt2rRxuMbDw/Y/lY+Pjzp27JhhXdeuXW2agj/++KNdTcFVq1bZNFlDQ0PVtGlTBxIDAAAAyMmaVyyslSPb6qdNJzVj4wlFxiTK3c0kkySLUk8ZLuznpYeblVX/pmUcniEYk5CshGSzCvl5uSR/jrB9lrTyA8frEqKkGQ9KfWZKlTP+vQ4A8iJDm4JIr2/fvnr99dcVExMjSVqzZo1Wrlyp9u3b37bGYrHo3Xfftbk3ePBgubmxmTAAAACQl4QG+uiFu6vo6faVtOrABR29GKOYhGT5eXuoYoif2lUr6tShIilmi56bs0OHzkdr8qONVamovwvS5wCVOkpFa0gXHNu/XZKUHCfN7iv1/EGq2d3waACQ09FlcrGiRYvq6aeftrn3xBNP6OzZs7etGT16tNasWWO9DgoK0ksvveSyjAAAAACyl6e7m+6pWUzD2lbUi/dW1bC2FXVPzWJOnzI8evl+/bX/vE5GxurB8WFaf+SSwYlziIBQ6dFlUsmGztWbk6T5g6XtMzN+FgDyGJqCWeDll19WsWLFrNfHjx9XixYt9Msvv9gcpHL69GkNHTpUb7zxhk39G2+8oUKFCmVZXgAAAAC518yNJ/TDuv+2IoqKT9bAyf9q3pZT2ZjKhQoUkgYukcq1cq7eYpaWjJA2fmdsLgDI4WgKZoFChQpp7ty58vH5bw+QEydOqFu3bipUqJAaNGigChUqqFy5cpo4caJNbbdu3WwOOAEAAACA2/nn0EWN+mVvuvvJZotenr9Ln6w4IPOdTjXJrbwDpAHzpSr3OT/Gilel1Z+knmYMAPlAlu4peObMGe3atUuRkZGKjIyUlNowK1SokOrUqaOSJUtmZZws1bp1ay1btkwPPfSQ9XuXpKtXr2r79u23rOnfv78mT54sk8mUVTEBAAAA5FIHz0Xr6VnblHKHpt93q4/qxOUYjeldTz6e7lmYLgt4+kh9ZkiLhkp75js3xuqPUg8huecDid/DAORxLm8K7t+/X2PHjtXy5ct1+vTpOz5bqlQpPfDAA3rmmWdUrVo1V0fLcu3bt9e+ffv07rvvatq0aYqNjb3lc/Xr19ebb76pBx98MIsTAgAAAMiNLkYn6LGpmxWdkJzhs8t3n9OZqxv1/cCGKhrg2InGOZ67p/TgpNSZg1unODfGhm9TG4MPfCW55bHGKQDcwGSxuGZu9JUrVzRkyBAtXLhQkmTva9JmxfXq1UsTJkxQwYIFXREv28XFxWn9+vXav3+/rl69Ki8vL5UsWVJNmzZVpUqVDHvPunXr1KrVf3trrF27VnfddZdh4wMAAADIXvFJKeozaaN2nrrqUF3JYF9NfrSxqhYLcE2w7GSxSH+NksK+dn6Mmg9KPSZKHl7G5QIAF3K0B+SSmYJbt25V9+7ddfbsWWsz8OYlsBndnz9/vjZs2KDFixerQYMGroiZrXx9fdWhQwd16NAhu6MAAAAAyKXMZov+N2+Hww1BSTpzNU49v1uvcQMaqE2VEOPDZSeTSer4ruQdKK1837kx9i6UEq9LvadLnr7G5gOAHMDwg0aOHDmi+++/X2fOnJHFYpHJZJLJZJLFYpHFYpGvr6+qVq2qpk2bqmnTpqpatap8fX2tX7/x+dOnT+u+++7TsWPHjI4JAAAAALleYopZSSnOL/66npCsx6Zu1oyNJwxMlUOYTFLrF6X7PnN+jMN/SDN7SfFRxuUCgBzC0KagxWJRr169dPHiRZvmXokSJTRq1Cjt3r1bUVFR2rdvnzZs2KANGzZo3759ioqK0u7duzVq1CiVLFnSpjl48eJF9erVy8iYAAAAAJAn+Hi6a8LDDfXEXeWdHiPFbNFbi/fo/aX77nhISa7VdIjUfYJkcnJ/wBPrpOldpdjIjJ8FgFzE0KbgjBkztGvXLpuZgc8//7wOHjyoUaNGqWbNmnJzS/9KNzc31axZU6NGjdLBgwf1v//9z2YPwp07d2rGjBlGRgUAAACAPMHdzaQ3H6ihD7rXkrub8yfm/rjuuJ6asVUxdhxWkuvU6yf1nia5O7k/4Nnt0pT7pKgIY3MBQDYytCn4zTffSJJ1pt/HH3+sMWPGqECBAnaP4evrq88//1yfffaZdRyLxaKxY8caGRUAAAAA8pSHm5XVlEcbK8Db+a3j/9p/Xg9N2KCIa3EGJsshqneR+s+VPO3//dTGxQPSlE7SlXBDYwFAdjGsKXjx4kVt27bNuuy3Y8eOevnll50eb+TIkbr77rutMwa3b9+uixcvGhUXAAAAAPKc1lVCNH9YC5UMdv5gjH0RUeo+Lkx7zlwzMFkOUbG99MhiyTvIufor4dLkTtKFA0amAoBsYVhTcMOGDdYlw5L0wgsvZHrMG8ewWCzauHFjpscEAAAAgLysarEALR7RUvVKBzs9xvmoBD00YYP+3HfeuGA5RZmm0qNLpQJFnKuPjkhdSnx2u7G5ACCLGdYUvHDhgs11+/btMz1mu3btJEkmU+q+GOfP58F/kAAAAADAYCEB3pozpJk61y7u9BhxSSkaMmOLflh7zGbP9zyheB3psRVSYEnn6uMipWldpRPrjc0FAFnIsKbgpUuXrJ8HBwfLy8vJDVxv4O3trYIFC1qvL1++nOkxAQAAACA/8PF01zf96mtEu4pOj2GxSB8s26+3luxRcorZwHQ5QJHKqY3BQhWcq0+IkmY8KB3+y9hcAJBFDGsK+vn5WT+PiYkxalhdv37d+rkjB5YAAAAAQH7n5mbSS/dW02e96sjT3fmTiWduPKnHpm1RdHySgelygOAy0uAVUtGaztUnx0mz+0p7FxsaCwCygmFNwZCQEOvnSUlJOnjwYKbHPHz4sJKS/vtH58Z3AAAAAADs81Cj0pr+WFMF+Xo6PcaaQxfV67sNOn0l1sBkOUBAaOoegyUbOVdvTpLmD5a2zzQ2FwC4mGFNwapVq0r6b/+/WbNmZXrMtDHS9q9IewcAAAAAwDHNKxbWwuEtVLaw8yuwDp6PVvdxYdp+8oqByXKAAoWkgYul8q2dq7eYpSUjpI3fGRoLAFzJsKZg/fr1VbRoUUmpTbwvvvhCR44ccXq8Y8eO6fPPP7c2GYsWLar69esbkhUAAAAA8qOKIf5aNLylmpQr5PQYl64nqu+kjVq+O8LAZDmAd4DU/2epyn3Oj7HiVWntF8ZlAgAXMqwpKEk9e/aUxWKRyWRSXFycOnTooAMHDjg8zpEjR9SxY0fFxsZax+vVq5eRUQEAAAAgXyrk56UZTzRRj/pOnrwrKSHZrOGztmn86iN562RiTx+pzwyp9kPO1bt5SKG1jc0EAC5iaFPwrbfesh4GYjKZdOrUKTVo0EDvvPOOLly4kGH9pUuX9P7776tevXoKDw+3zhIsUKCA3njjDSOjAgAAAEC+5e3hrjG96+p/d1fJ1DifrjioVxbsUmJyHjqZ2N1T6jFJavSYg4Um6cFJUpV7XBILAIzmYeRgxYoV0+jRo/Xcc8/JZDLJZDIpPj5e77//vj766CO1aNFCjRo1Uvny5RUYGChJioqKUnh4uLZs2aL169crOTnZOjsw7f/9+OOPVaxYMSOjAgAAAEC+ZjKZ9GyHyipbuIBe+nmXElOca+zN23JapyLjNOHhhgoq4PxBJjmKm5vUeUzqkuKwr+2r6fK1VKuna3MBgIEMbQpK0jPPPKMTJ05ozJgx1sagxWJRcnKy1q5dq7Vr1962Nm3aedoMQUkaOXKkRowYYXRMAAAAAICkbvVKqmSwr4bM2KrImESnxthw7LJ6fBemyYMaq1wRP4MTZhOTSbr7PcknSPr7vTs/e8+HUsNBWZMLAAxi6PLhNJ9//rkmTJggX19f62y/tEafxWK55Yckmyair6+vJk6cqE8//dQVEQEAAAAA/69RuUJaNLyFKoY439A7djFGPcaHaXN4pIHJcoBWI6X7P7/919u8IrV4OuvyAIBBXNIUlKQhQ4Zo165dGjp0qAoUKGDT/JNk0yiU/msWFihQQMOHD9fu3bv15JNPuioeAAAAAOAGZQv7aeGwlmpRsbDTY1yJTdKA7zdp8fYzBibLAZo8KfWYKJncbe83HSa1fS17MgFAJhm+fPhGFSpU0Pjx4/XJJ5/on3/+0fr167Vr1y5FRkbqypUrkqSCBQuqcOHCql27tlq0aKE2bdooICDAlbEAAAAAALcQVMBT0x5rojcX7dHcLaecGiMxxazXFu5Wi0qFVTTAx+CE2ahuX8nLT5r/mJSSKNV7WLr3o9RlxgCQC7m0KZgmICBADzzwgB544IGseB0AAAAAwEme7m76uGdtVQjx0+jfDjhcbzJJX/Wtl7cagmmqd5H6z5V2/Sx1HZt6IAkA5FJZ0hQEAAAAAOQeJpNJT7WpqLKFC+j5uTsUn2T/ycSv3VdN99Ys5sJ02axi+9QPAMjl+LMGAAAAAOCWOtUqrrlDmiskwNuu5/s1KaMnW1VwcSoAgBFoCgIAAAAAbqtu6WAtHtFS1Yrdee/3uyoV0XvdatocKAkAyLloCgIAAAAA7qhksK9+HtpcbaqE3PLrlYr6a9yABvJ051dMAMgtDP2JffLkSVWsWFEVKlRQhQoV9OWXXzo91pgxY6zjVK5cWRcuXDAwKQAAAADAEQE+nvpxUCMNbF7W5n5hPy9NebSxgnw9sylZLmexSEtfkPYuyu4kAPIZQ5uCP/74o44fP67w8HBFRESoX79+To/Vr18/nT17VuHh4Tp27JgmT55sYFIAAAAAgKM83N30XrdaGtWlhtxMkpeHmyYNbKjShQpkd7TcyWKRfn9D2jJZmv+YtG1GdicCkI8Y2hRcvHixpNSTqu6++24VK+b8iVPFixfXPffcY72eP39+ZuMBAAAAAAwwuGV5fT+wkcb0rquGZQtld5zc659PpI3jUj+3mKVfnpY2jM/eTADyDcOaghcvXtTu3butm8o++OCDmR6zR48ekiSLxaIdO3YoMjIy02MCAAAAADKvQ/VQPVCnRHbHyL02jJdWj05///fXpNUfp84iBAAXMqwpuGvXLkmpDTxJatq0aabHbNasmfVzi8Wi3bt3Z3pMAAAAAACy1bYZqc2/21k9OnVZMY1BAC5kWFPw6NGj1s9NJpOqVauW6TGrVq0qk8lknX145MiRTI8JAAAAAMiZklLM2R3B9fYukn59NuPnNo6TfnlGMqe4PhOAfMmwpuDVq1etnwcGBlobeZnh5uamoKCgW74DAAAAAJB3pJgtemrGVr2/dJ9SzHl0htzhP6UFT6buH2iP7TOkBY9LyYmuzQUgX/IwaiDLDdOaU1KM+0vGjWMlJvKDEAAAAADyog+W7dPKAxckSScux+jrvvXl523Yr6zZLzxMmvuwZE5yrG7vIinhutR7uuTFKc8AjGPYTMEiRYpYP79+/boSEhIyPWZCQoKio6Ot1wULFsz0mAAAAACAnGX6hnBNCQu3Xv+1/4IemrBBEdfisi+U0S4dkpLjnas98qc0q5cUH2VsJgD5mmFNwZCQEJvrTZs2ZXrMf//9V9J/sxBvfgcAAAAAIHdbdeCC3vllb7r7+yKi1H1cmPacuZYNqVyg0WCpx0TJ5O5c/YkwaXpXKeaysbkA5FuGNQUbNGggSda9BBcvXpzpMRcuXGhzXbt27UyPCQAAAADIGfZHROnpn7bpdlsIno9K0EMTNujPfeezNpir1O0r9Z4muXs5V392uzT1fikqwthcAPIlw5qCpUqVUuXKlSWlzuybOHGizp496/R4Z86c0aRJk6xNxtKlS6tKlSqGZAUAAAAAZK8LUfF6fOpmxSTeeU/6uKQUDZmxRT+sPWazl32uVb2L1H+e5Onk/oAXD0iT75UijxubC0C+Y1hTUJJ69eoli8Uik8mkuLg49ejRQ3Fxju8BERsba61NG69nz55GRgUAAAAAZJO4xBQ9MX2Lzl6zb489i0X6YNl+vbVkj5JT7Dy5Nyer2E4auETyCXKu/uoJacp90oUDxuYCkK8Y2hQcOXKk/P39JaUuI96yZYtatWqlQ4cO2T3GwYMH1apVK23ZssU6S9DX11evvPKKkVEBAAAAANnAbLbohbk7tOu043sFztx4UoOnblZUvIMn+OZEpZtIjy6T/JzcOz86IrUxeHa7sbkA5BuGNgULFSqkt99+2zql22KxaNu2bapdu7b69++vZcuWKTIyMl1dZGSkli5dqr59+6pOnTrasWOHTCaTdZbgG2+8oaJFixoZFQAAAACQDU5ExmrDMecPy1h7+JJ6fbdepyJjDUyVTYrVlgavkAJLOVcfFylN7SKFhxmbC0C+YLK4YFOG/v37a86cOdaZfmnNvTRBQUEKDg6WJF29elXXrv33F6Ibn7VYLOrTp49mz55tdMR8Y926dWrVqpX1eu3atbrrrruyMREAAACA/O7oxet6bOpmnbjsfGOviL+Xvh/YSPXLFDQwWTa5ekqa3k2KPOpcvYeP1GemVPluY3MByFUc7QEZOlMwzZQpUzRw4EDrjMG0WX9pH1evXlV4eLjCw8N19epVm6/d2BAcNGiQpk6d6oqIAAAAAIBsUjHEX4uGt1STcoWcHuPS9UT1nbRRy3fngZN4g0tLj62QQms5V58cL83uK+1ZaGwuAHmaS5qC3t7emjp1qiZNmqSiRYvaNAfv9CGlNgOLFSumH3/8UVOmTJG3t7crIgIAAAAAslEhPy/NeKKJetQv6fQYCclmDZ+1TeNWHcn9JxP7F5UeXSqVauxcvTlZWvC4tG26sbkA5FkuaQqmeeKJJxQeHq5x48apffv28vHxsZkVeOOHr6+vOnTooIkTJ+r48eMaPHiwK6MBAAAAALKZt4e7xvSuq//dXSVT43z2+0G9PH+XEpNz+cnEvgWlRxZL5Vs7V28xS788I20YZ2gsAHmTh6tf4O3trWHDhmnYsGFKSkrS/v37dfHiRV2+nLqxbOHChRUSEqLq1avL09PT1XEAAAAAADmIyWTSsx0qq2zhAnrp511KTHGusffz1tM6dSVWEx5uqOACXganzELe/lL/n6X5g6WDy50b4/fXpfgoqe2r0g37+wPAjVzeFLyRp6en6tSpk5WvBAAAAADkAt3qlVTJYF8NmbFVkTGJTo2x8VikHhy/XpMfbaxyRfwMTpiFPH2k3tOlxcOl3fOcG+Ofj6WEKOnej2gMArglly4fBgAAAADAXo3KFdKi4S1UMcT5ht6xSzHqMT5Mm8MjDUyWDdw9pR4TpUaPOT/GxvHSL09L5hTjcgHIM2gKAgAAAAByjLKF/bRwWEu1qFjY6TGuxCZpwPebtGj7aQOTZQM3N6nzGKnl886PsX2mNP8xKdm52ZcA8i6aggAAAACAHCWogKemPdZEfRqVdnqMxBSzXpi7U2P+PJS7TyY2maS735U6jHJ+jH2LpTn9pcRYw2IByP2ydE/BG508eVIrV67UkSNHdPnyZRUoUEChoaGqX7++2rZty6EjAAAAAJCPebq76eOetVUhxE+jfzvg9Dhj/z6s8Esx+rRXHfl4uhuYMIu1+p/kHSAtf9G5+iN/SjN7Sv3nSj6BxmYDkCtleVNwx44dev311/X777/f9hl/f389++yzev311+Xr65uF6QAAAAAAOYXJZNJTbSqqbOECen7uDsUnOXcy8S87z+rs1ThNfKShCvt7G5wyCzV5UvIOlBYPkyxO7BN4cr00rYv08ELJz/nl2QDyBruXDycnJ+uRRx5R//79rR+nTp1y6GVTp05V8+bN9fvvv8tisdz2Izo6Wh999JHq1aunM2fOOPxNAQAAAADyjk61imvukOYKCXC+obflxBX1GL9eRy5cNzBZNqjbJ/VkYncv5+ojdkhT75eizhoaC0DuY3dTcP369Zo1a5bmzp2ruXPnau/evSpd2v79HX799Vc9/vjjSkhIkMVikclkuuOHxWLR4cOH1bZtW0VG5vJTowAAAAAAmVK3dLAWj2ipasUCnB7jZGSsHhwfprAjlwxMlg2qPyD1nyd5FnCu/uIBaXInKfK4sbkA5Cp2NwVXrFghSdYNWp955hm7X3LlyhUNGjTIphmYNtatPiRZnzl27JheeeUVu98FAAAAAMibSgb76uehzdWmSojTY0TFJ2vQ5H81d/NJA5Nlg4rtpIFLJJ8g5+qvnpAOLDM2E4Bcxe6mYFhYmPVzLy8v9enTx+6XvP/++7p69Wq6ZuB9992nP/74Q5GRkYqPj9eRI0f05ZdfKiQkxNpAtFgsmjJlivbt2+fAtwUAAAAAyIsCfDz146BGGti8rNNjJJstemXBbn382wGZzbn4ZOLSTaRHl0l+TjRJmz8tNR9hfCYAuYZdTUGLxaLt27dbZ/l17NhRAQH2TdmOi4vT5MmTbRqCJpNJr7zyipYtW6aOHTsqODhYXl5eqlChgp577jnt2rVL1apVs3n/9OnTnfj2AAAAAAB5jYe7m97rVkujutSQm8n5cSb8c1QjftqmuEQnDu3IKYrVlgavkAJL2V/TYKB0zweSKRP/8QDkenY1BY8dO6br1//bjLVTp052v2Dx4sWKioqS9F9DsGnTpho9evRta4oWLaoFCxbI3d3dOltw3rx5dr8TAAAAAJD3DW5ZXt8PbKQCXu5Oj/HbnnPqO2mDLkTHG5gsixWpJD22QipUMeNnaz4oPfAVDUEA9jUFjx9P3Xw0bb+/xo0b2/2C33//Pd29UaNGZVhXvXp19enTx/rOEydOcOAIAAAAAMBGh+qh+nlocxUL9HF6jJ2nr6n/95uUnGI2MFkWCy6d2hgMrXX7ZyrfI/WYKLk530QFkHfY1RQ8deqUzXWtWnf4IXOTf/75x7p0WJKKFSume+65x67am/ct3Llzp93vBQAAAADkDzVLBGnJ0y1Vq2SgU/Umk/TyvVXl4W73tvs5k39R6dGlUqlbTOQpe5fUe7rk4ZX1uQDkSHb9xEtb/itJ3t7eKlDAvmPPIyIidOLECUn/LR3u2LGjTZPwTho2bCjpv5OIT57M5adDAQAAAABcIjTQR/Oeaq6O1UMdrn3j/uq6p2YxF6TKBr4FpUcWS+Xb/HevRH2p32zJ0zfbYgHIeexqCsbExFg/9/f3t3vwLVu2pLvXqlUru+uLFy8uL6///ooRHR1tdy0AAAAAIH8p4OWhiY801JOtyttdM6BpGT1+l/3P5wre/lL/eVLVzlJINenhhZKPc7MoAeRdHvY8dGNj7sYDRzKyefPmdPcaNGhgd70kBQQE6PLlyzKZTDQFAQAAAAB35O5m0huda6hcET+9vWSvUsyW2z7bqnIRvdO1pt2r2XIVTx+p9zQp/ppUoFB2pwGQA9k1UzA4ONj6eUJCgq5cuWLX4Bs3brS59vT0VO3ate1PJykuLs76A9rDw64eJgAAAAAgnxvQtKymPNpYAd63/j2ySqi/xg1oIM/cvo/gnbh7Sn5FsjsFgBzKrp9+xYrZ7q2wffv2DGuSkpK0adMmmUwm6wnC9erVk6enp93h4uPjFRsba70OCAiwuxYAAAAAkL+1rhKiBcNbqGSw7V56Rfy99OOgxgr0sf/3UwDIa+xqCt584MfChQszrFm5cqXNcl+TyaS2bds6FO706dM210WLFnWoHgAAAACQv1UJDdDiES1Vr3SwJMnbw02TBjZS6UL2HaAJAHmVXU3B4sWLq0yZMpJSTxGeOnVquobdzb777rt09+6//36HwqUtP06baVi5cmWH6gEAAAAACAnw1pwhzfRAneIa07ueGpQpmN2Rcq8Dy1L3KQSQ69m9ecLAgQNlsVhkMpkUGxurBx98UFFRUbd8dsGCBfrll19sNmstXbq0Wrdu7VC4sLAw6+cmk4mmIAAAAADAKT6e7vqmX311rlM8u6PkXrvnS3MGSNO6SjGXszsNgEyyuyk4ZMgQ+fj4SEpt0G3dulU1atTQl19+qa1bt+ro0aNas2aNnn32WfXv39/aEExrJA4fPtyhYGaz2aaxWLNmTev7AQAAAABwVJ48ZTirHFwhLXpKkkWK2CFNvV+KOpvdqQBkgt3H+ZYqVUrvvvuuXnnlFevhIWfPntWLL76Y7tm0RmCaEiVK6Nlnn3Uo2B9//KGIiAiZTCaZTCbdddddDtUDAAAAAAADHF8jzRsomZP/u3fxgDS5kzRwiVSofPZlA+A0h85eHzlypHr27Glt+qU1B2/+uHGWoIeHh2bNmuXwLL/vv//eOoYkhw8pAQAAAADAlZJTzBo5b6e2n7yS3VFc5/QWaXY/KSUh/deunkhtDF7Yn/W5AGSaQ01BNzc3zZ07V8OGDZMkm+bgjR9pX/P399fPP//s8F6Ce/bs0eLFi61jeXp6qlOnTg6NAQAAAACAK72/dJ8WbDutvpM2avnuiOyOY7zz+6SZPaXE67d/5vo56YcO0rKR0t/vS2vHSPuXSilJWZcTgFMcagpKqY3BcePGadOmTerbt68CAwPTzRQsVqyYnn76ae3fv1/dunVzONSoUaOsY0mpswQDAgIcHgcAAAAAAFeYEnZc0zackCQlJJs1fNY2jV99xPp7bK53+ag0o7sUfzXjZxNjpM0/SGFfSqs+kOYOkL6oJq36SIrKg81SII+we0/BmzVq1Eg//fSTUlJSdObMGZ0/f14mk0mhoaEqXbp0pkJ99dVXGjNmjPU6KCgoU+MBAAAAAGCUv/ef1/tL96W7/+mKgwq/FKMPuteWl4fDc3ByjmtnpOndpevnHaszp/z3eewlac3n0oZvpX5zpfKtDI0IIPOcbgqmcXd3V5kyZVSmTBkj8khSppuKAAAAAAC4wr6zUXpm9naZbzMhcN6W0zoVGacJDzdUUAHPrA1nlD/ekK6dzPw4lhQpKS51xuEji2kMAjlMLv7TBQAAAAAAWed8VLwen7ZZsYkpd3xuw7HL6jE+TOGXYrIomcEe+FIq1diYsSzm1I/ZfVlKDOQwNAUBAAAAAMhAbGKyHp+2WRHX4u16/tilGPUYH6bN4ZEuTuYCvgX/f2ZfG2PGs5ilpFhp61RjxgNgCJqCAAAAAADcQYrZoufm7NCeM1EO1V2JTdKA7zdp8fYzLkrmQt7+Uv95UtXOxoxnMUtbfuRUYiAHoSkIAAAAAMAd/L73nP7c5+ChG/8vMcWs5+fu0Jd/Hsp9JxN7+ki9p0l1+hgzXsxF6fAfxowFINNoCgIAAAAAcAf31Sqm1+6rJpPJ+TG+/vuwnp+7Q/FJd96PMMdx95S6T5BKNsr8WCZ36dKhzI8DwBA0BQEAAAAAuAOTyaSn2lTUdwMayMfT+V+jl+w4q4d/2KTL1xMMTJcF3NykCm0lUyZbCCY3KeG6IZEAZB5NQQAAAAAA7NCpVnHNHdJcIQHeTo+x5cQV9Ri/Xkcu5LLmmJefMjVVUkrdV9Db35g8ADKNpiAAAAAAAHaqWzpYi0e0VLViAU6PcTIyVg+OD9P6I5cMTOZiRapI5kwufbakpI4DIEegKQgAAAAAgANKBvvq56HN1bZqiNNjRMUna+DkfzVv8ykDk7lQlXulAkUyN4bJTSrdzJg8ADKNpiAAAAAAAA4K8PHUDwMbaVDzsk6PkWy26OUFu/TxbwdkNufwk4ndPaXGj6ceFuIsi1la+Z5xmQBkCk1BAAAAAACc4OHupne71dI7XWrILRPb7U3456hG/LRNcYk5/GTihoMlT5/MHTiydap0dJVhkQA4j6YgAAAAAACZ8GjL8vphUCP5eTk/i+63PefUd9IGXYiONzCZwQKLS/3mpjYFM9MY/OVZKSHauFwAnEJTEAAAAACATGpfLVQ/D22h4kE+To+x8/Q19Ri3XgfORRmYzGDlW0mPLJY8Czi/lPjaSemvd4xMBcAJNAUBAAAAADBAjRKBWjyipWqVDHR6jDNX49Truw1affCCgckMVr6V9PQWqfVLzh8+svkH6fgaY3MBcAhNQQAAAAAADBIa6KN5TzXX3TVCnR7jekKyHpu6WTM2hBsXzGiBxaV2r0kjD0h9f5Kq3u/4GEuelhJjjM8GwC65pil47Nix7I4AAAAAAECGCnh5aMLDDfVkq/JOj2G2SG8t2at3f92rlJx8MrG7p1Sts9RnllT2Lsdqr56Q/nrXNbkAZChHNwWvX7+uyZMnq3Xr1qpSpUp2xwEAAAAAwC7ubia90bmGPuxRS+6ZOJp4Sli4hkzfopiEZAPTuYCbm9R1rOTh61jdvxOl8DDXZAJwRzmyKbhy5UoNHDhQxYsX15NPPql169bJYsnBfxkBAAAAAOAWBjQtqymPNlaAt4fTY/x94IIemrBBEdfiDEzmAoUrSh1HOV63ZISUGGt8HgB3lGOagseOHdPbb7+t8uXL6+6779asWbMUExNDMxAAAAAAkKu1rhKiBcNbqFRBB2fR3WBfRJS6jwvTnjPXDEzmAk2ekko3c6zmynFp5QeuyQPgtrK1KXjj8uDKlSvrww8/1IkTJ2SxWGSxWGQymWQyOT/NGgAAAACAnKBKaIAWDW+p+mWCnR7jfFSCHpqwQX/sPWdcMKO5uUndxkkePo7VbRwvndzomkwAbilbmoI3Lw8OCwu7ZSMw7bpNmzYaP358dkQFAAAAAMAQIQHemv1kM3WuU9zpMeKSUvTUzK36Ye2xnLuyrkglqf2bDhZZUpcRJ+XwJdJAHuL8pgYOOnbsmKZOnaoZM2bo5MmTkmTzA+zGRqAkNW3aVH379lXv3r1VvLjzPzABAAAAAMgpfDzd9U3f+ipf2E/frjri1BgWi/TBsv06dy1ebz5Qw+CEBmk2XNq3RDq92f6ay0ekVR9K97CUGMgKLm0KXr9+XfPmzdPUqVMVFpZ6mtDtGoEWi0V169ZV37591bdvX5UtW9aV0QAAAAAAyBZubia9eG9VlSvip9cW7lJSiuMz/txMUotKhV2QziBu7lK38dKEu6SUBPvrNoyTanSXSjVyWTQAqVzSFFy5cqWmTp2qRYsWKTY29QShtGbgzTMC05YIf/rppxo5cqQr4gAAAAAAkOP0alhKJYN9NXTmVl2LS3Ko9q0Haqh9tVAXJTNISBWp3evSXw6cSGwxS4uHS0+tkTwd3JcQgEMM21Mwo9OD0/YKTLtu27atzazBgIAAo6IAAAAAAJArNK9YWIuGt1C5wgXsrhnYvKwebVHOdaGM1PxpqUQDx2ouHZR2zXVNHgBWmWoK2nt6cNp1pUqV9P777+v48eNauXKlJHG6MAAAAAAgX6sQ4q+Fw1uqSblCGT7btmqI3n6gRu75XdrdQ+o+XnL3su957yCp67dSg4GuzQXAueXD9i4PtlgsKliwoPr06aOBAweqWbNmBsUGAAAAACDvKOTnpRlPNNFrC3Zr4fYzt3ymWrEAfdOvvjzcDVv0lzWKVpfavCKtfP/Oz1W+V+rylRRYIktiAfmd3U3BO50enDYjMO2eh4eHOnXqpEGDBqlLly7y8rLzLwIAAAAAAORT3h7u+qJ3XZUv4qcv/jxk87Ui/t768dHGCvDxzKZ0mdTyeWn/r1LEjvRf8wmSOn0i1e0r5ZYZkEAeYHdTsFKlSjZ7AkrpDw2pX7++Bg0apP79+6tIkSIGRwUAAAAAIG8zmUx6pkNllSlcQC/N36XEZLN8PN3046BGKhnsm93xnJe2jHhiG8l8w6EqVe+XHvhSCiiWfdmAfMrh5cM3Lw8uXry4BgwYoEGDBqlmzZqGBwQAAAAAIL/pVq+kShX01VMztur9brVUt3RwdkfKvNCaUuuXpNUfSb4Fpfs+k2r3YnYgkE2c2lMwbYnw22+/rTfeeCP3bHAKAAAAAEAu0bBsIa1+qZ38vZ361T1navU/KTFaav6MFBCa3WmAfM2p3UlNJpOSk5M1atQo1a5dW5988onOnLn1RqgAAAAAAMA5eaohKEnuntI9H9AQBHIAh5qCN+8naLFYtG/fPr3++usqV66c7r77bs2aNUtxcXGGBwUAAAAAAABgDLubgps3b9awYcNUsGBB636CaacOWywWpaSkaOXKlRo4cKBCQ0M1ePBgrVq1ypXZAQAAAACAA5JTzJq05qjik1KyOwqAbGZ3U7Bhw4YaN26czp49q7lz5+r++++Xm5ubTXNQSp1NeP36dU2fPl0dO3ZUuXLl9NZbb+nQoUMZvAEAAAAAALiKxWLRO7/u1UfLD2jAD5t0+XpCdkcCkI0c3lPQy8tLDz30kJYuXarTp0/rk08+UY0aNW45e9BisejkyZP66KOPVL16dTVr1kzfffedrly54orvBQAAAAAA3MbksHDN3HhSkrT1xBV1Hx+mIxeiszkVgOzi1EEjaUJDQ/XSSy9p9+7d+vfffzV06FAFBwdb9x68uUG4efNmPf300ypRooR69uwpyXafQgAAAAAAYLy/9p3XB8v22dw7FRmnHuPXK+zIpWxKBSA7ZaopeKNGjRpp/PjxioiI0Jw5c3TffffddnlxQkKCFi9ebL0nSdevXzcqCgAAAAAA+H97zlzTs3O261ZzcqLjkzVo8r+au/lk1gcDkK0Mawqm8fLyUu/evbVs2TKdOnVKH3/8sapXr55ueXGatJmEL730kho2bKjPP/9cJ0/ywwgAAAAAgMw6dy1ej0/brNjE2x8skmy26JUFu/XxbwdkNrOaD8gvDG8K3qhYsWJ6+eWXtWfPHm3atElPPfWUgoKCrA3CNGmNwe3bt+uVV15R+fLl1bJlS3377bc6f/68KyMCAAAAAJAnxSQk6/Fpm3U+yr4DRSb8c1QjftqmuDs0EHOUhOvS0VXZnQLItVzaFLxR48aN9d133+ncuXOaPXu2OnXqZF1eLKXff3Djxo167rnnVKpUKXXo0EE//PBDVkUFAAAAACBXSzFb9Nyc7dp7Nsqhut/2nFPfSRt0ITreRckMcmy1NL659FMf6eKh7E4D5EpZ1hRM4+XlpT59+mj58uU6efKkRo8erWrVqt1yebHFYlFKSopWrVqlp556KqujAgAAAACQK32z8rD+2n/Bqdqdp6+px7j1OnDOsYZiloiPkn59TpreTbp2UkpJkJaMkMy5ZHYjkIPY3RSsUKGC9WP27NmGvLx48eJ65ZVXtHfvXm3cuFFDhgyxWV588/6DAAAAAAAgY/2alFGtkoFO15+5Gqde323QqoPONRZd4shfqbMDt061vX/6X2nThGyJBORmdjcFw8PDFR4erhMnTig6OtrwIE2aNNGECRMUERGhn376Sffee691OTEAAAAAALBfaKCP5j3VXPfUCHV6jOsJyXp86mZN3xBuXDBnxF1NnQ04s6cUdfrWz/z9nnT5aJbGAnI7h5YPZ8WsPW9vb/Xt21e//fabTp48qY8++khVq1Z1+XsBAAAAAMhLCnh5aMLDDTWkdQWnxzBbpLeX7NW7v+5VSnacTHzoj9TZgdtn3vm55HhpydOS2Zw1uYA8IMv3FHREiRIl9Oqrr2r//v1av359dscBAAAAACBXcXMz6fX7q+ujHrXl7ub8RJ8pYeEaMn2LYhKSDUyXgb/fl356SIo+a9/zJ9dLm793bSYgD8nRTcEbNW3aNLsjAAAAAACQK/VvWkZTBzdWgLeH02P8feCCHpqwQRHX4gxMdgcV2zle89c7UuQxw6MAeVGuaQoCAAAAAADntaocooXDW6hUQV+nx9gXEaXu48K058w1A5PdRrm7pCZDHKtJipV+eZZlxIAdaAoCAAAAAJBPVA4N0KLhLVW/TLDTY5yPStBDEzboj73njAt2Ox1GScFlHasJXytt+dE1eYA8hKYgAAAAAAD5SEiAt2Y/2Uyd6xR3eoy4pBQ9NXOrflh7TBaLCw8g8faXun7jeN2fo6QrJ4zPA+Qhzm8mAAAAAAAAciUfT3d907e+KhTx0zcrjzg1hsUifbBsv/45dFFNyxdSfJJZBbzdVTHEX+2rFZWnu0HzkCq0kRo9Jm2ZbH9NUoz0yzPSwCWSyfkDVoC8jKYgAAAAAAD5kJubSSPvqaqyhf302sJdSkpxbsbf2sOXtPbwJXm4mWSRlGK2qJCflx5uVlYDmpZRaKBP5sPe/Z50+E/p2in7a47/I22dKjUanPn3A3kQy4cBAAAAAMjHejUspRmPN1WQr2emxkk2W5RiTm0sRsYk6tuVh9X+89XacPRy5kN6B0hdxzpe98db0lUHGolAPuLUTMFDhw5pzZo1RmfJUOvWrbP8nQAAAAAA5HXNKhTWouEt9NjUzQq/HGvImGZL6t6Dj/y4STMeb6rmFQtnbsCK7aUGA6Vt0+2vSYyWfn1Wenghy4iBmzjcFLRYLPryyy/15ZdfuiLPbZlMJiUnJ2fpOwEAAAAAyC8qhPhr0fCWemrGVv0bHmnImKkTBy16YvpmrRzZNvNLie/5QDrytxR1xv6aoyul7TNSG4oArJxaPmyxWLLlAwAAAAAAuE5BPy/NeKKJHqxf0rAxzRYpLjFFP206mfnBfIKkLk4sI/79DemaA41EIB9wqiloMpmy9AMAAAAAAGQNbw93fdG7rkbeXcWwMc0WaebGE0pKMWd+sModpXoPO1aTECUtfT71yGQAknLJTEEAAAAAAJB1TCaTnulQWWP71ZeXhzFnlF6OSdSqAxcMGUv3figFFHes5vAf0s7ZxrwfyAMc3lPQZDLpgw8+UP/+/V2RBwAAAAAA5BBd65ZQyWBfPfLDJsUmpWRqLHc3k45ejDEmmG+w1OVr6afejtWteFWq0E4KdLChCORBTp0+XLhwYZUtW9boLAAAAAAAIIdpWLagejYspRkbT2RqHJOkmAQDDxCtcq9Up6+0a479NfHXpKUvSP1mcxox8j1j5gADAAAAAIA8q3iwj9zdMtdEs0jy83ZqbtLtdRot+Yc6VnPoN2n3z8bmAHIhmoIAAAAAAOCOKob4K8WcuT3/U8wWVQzxMyjR/ytQSHrgS8frlr8kRZ83NguQy9AUBAAAAAAAd9S+WlEV8vPK1Bie7ia1q1bUoEQ3qNZZqtXLsZr4q9Ky/3EaMfI1moIAAAAAAOCOPN3d9HCzssrMCuJ+TcrI091FbYj7PpX8QhyrObBU2rPANXmAXICmIAAAAAAAyNCApmXk6+nucGPQJMnP210j2lVySS5Jkl9hqfMXjtctf0m6ftH4PEAuQFMQAAAAAABkKDTQRz8Maiw3k8nuxqCbSXJ3M+nHQY0VGujj2oA1ukk1ezhWExcpLX/RNXmAHI6mIAAAAAAAsEvzioU14/Gm8vXKeMagm0ny9XLXzCeaqlmFwlkT8P7PpQIOvmvfYmnvYlekAXI0moIAAAAAAMBuzSsW1sqRbfVM+8rpDh9J6xMW9vPSM+0ra+XItlnXEJQkvyKpjUFHLRspxVw2Pg+Qg3k48rDFYpHJlIldRQEAAAAAQK4XGuijF+6uoqfbV9KqAxc0fcMJhQb6qFJRf1UM8VO7akVdd6hIRmr2kPYulPb/an9N7CXpt5ekXpNdlwvIYexuCg4aNMj6edWqVV0SBgAAAAAA5B6e7m66p2Yx3VOzWHZH+Y/JJHUeI4Wvk+Ku2F+3Z0FqQ7F6F9dlA3IQu5uCU6ZMcWUOAAAAAAAAY/gXle77TFr4hGN1S/8nlW0pFSjkmlxADsKeggAAAAAAIO+p3Uuqer9jNTEXpBWvuiYPkMM4tKdgRlJSUrR+/XqtWbNGO3bs0NGjR3X27Fldv35dCQkJ8vb2lr+/v0qUKKEKFSqoXr16at26tVq0aCEPD0OjOCwxMVEHDhxQeHi4zpw5o+joaCUlJSkwMFCFCxdWnTp1VL16dbm7uxvyvgsXLmjz5s06deqUrl69KpPJpODgYJUvX16NGjVSoUL8VQIAAAAAAKeZTNIDX0onwqT4a/bX7Zqbuoy46n2uywbkAIZ04o4cOaKxY8dq1qxZunr1qvW+xWKxeS42NlaxsbG6cOGCdu7cqUWLFkmSgoKCNGDAAD377LOqXLmyEZHsMn/+fP31118KCwvTgQMHlJycfMfng4KC1K9fPz333HOqVq2aw+8zm82aNm2axo8fry1bttzx2VatWmnEiBHq06ePw+8BAAAAAACSAopJnT6RFg91rG75y1KljpK7p2tyATlAppYPX716VUOGDFGNGjU0btw4XblyRRaLxfphMplu+3Hjc1evXtX48eNVo0YNPfnkk7pyxYGNQDPh+eef18SJE7Vnz54MG4KSdO3aNU2YMEF16tTRO++8k67peSfh4eFq2bKlHnvssQwbgpK0du1a9e3bV/fcc48uXLhg93sAAAAAAMAN6vaVKt9r//PF6kj9fqIhiDzP6abg+vXrVbNmTf34449KTk6+ZRNQkk3z704NQ4vFopSUFE2ePFm1atXSunXrDPsmHeHj46MqVaqocePGatiwocqWLWv9XtIkJSXp3Xff1RNP2Ldh6ZkzZ9SuXTtt3Lgx3ddKlCihRo0aqX79+ipcuHC6r//555/q2LFjljVKAQAAAADIU0wmqctXknfQnZ9z85TavSk9uVIqVjtLogHZyanlw4sWLVK/fv2UmJgoSTZNs7TZc56enqpWrZqKFCmioKAg+fn5KSYmRteuXdPly5d14MABm/obm4gRERHq0KGDfvrpJ/Xs2TNT32BGSpQooc6dO6t169Zq3ry5ypcvLzc3217plStXNH/+fL333ns6ffq09f7kyZN11113afDgwXd8x1NPPaXw8HCbe4MHD9arr76qKlWq2NzfsmWL3nrrLa1YscJ6b/fu3Xr55Zf1/fffO/ldAgAAAACQjwWWkDp9JC0Zceuvl6gvdRsvhdbI2lxANjJZHFkDK2nlypXq1KmTkpOTbRp5klS1alUNHjxYHTp0UO3ateXl5XXbcZKSkrR792799ddfmjp1qg4cOJCuuejh4aHffvtNHTp0cOZ7y9CuXbtUu3btdDMBb+fKlSvq2LGjtm3bZr1XvHhxnT59Ol0jMc3WrVvVqFEjm3uffPKJXn755Tu+64knntCPP/5ovTaZTDp16pRKlixpV9Y069atU6tWrazXa9eu1V133eXQGAAAAAAAZJW4xBT5ehlzyKcNi0Wa2VM6+vd/99y9pLavSS2eldyz9wBUILMc7QE5tHz4/Pnz6t27d7qGYM2aNfX3339r//79evnll9WwYcM7NgSl1JmEDRo00Msvv6x9+/bp77//Vo0aNawNRpPJpOTkZPXu3Vvnzp1zJKbd6tSpY3dDUJIKFiyomTNn2tREREQoLCzstjVLliyxua5Vq5ZeeumlDN/11Vdf2SwntlgsWrZsmd1ZAQAAAADITeISU/TR8v26+8t/FB2fZPwLTCap61jJKyD1umQjaeg6qdX/aAgiX3KoKfj8888rMjLS5qCQN998U9u3b1e7du0yFaRdu3bavn273njjDZsDPK5evarnn38+U2MbqXr16mrYsKHNvf3799/2+YMHD9pcd+/e3a5GpL+/v+6913Yj1CNHjjiQFAAAAACA3GHt4Yu656t/NGnNMZ2+EqfPfz+YcZEzgkpJ930i3f2+9PgfUkhV17wHyAXsbgru2bNH8+bNszYE3dzc9NVXX+m9996Th4cxHXUPDw+9//77+uqrryTJ+q758+drz549hrzDCBUrVrS5vnTp0m2fjYyMtLkuXbq03e8pU6aMzfXVq1ftrgUAAAAAIKeLjEnU/+bu0CM//qtTkXHW+9M3ntDWEy46cLP+AKnls5KbC5YoA7mI3U3BSZMm2SztfeKJJ/Tss8+6JNSzzz6rJ5980npKscVi0cSJE13yLmfEx8fbXAcHB9/22aAg29ON4uLibvNkejc/W6RIEbtrAQAAAADIqSwWixZvP6OOY/7Rwu1nbvF16bWFu5SYbM6GdED+YHdTcMGCBdYGXWhoqD777DNX5tJnn32m0NBQSak/LBYsWODS99nLYrFo8+bNNvduXk58o3r16tlc31x7J//++6/NdZMmTeyuBQAAAAAgJzoVGatBUzbr+bk7FBmTeNvnDp2/rgn/HM3CZED+YldT8MiRI4qIiJCUOktwwIABCggIcGmwgIAADRgwwDo78fz58zp8+LBL32mPyZMn6+zZs9bratWq3bFZ17t3b5s9BBcsWKDjx49n+J41a9Zow4YN1utixYrp/vvvdzI1AAAAAADZb+bGE7rnyzVac+iiXc9/u/KIjly47uJUQP5kV1Nw3759kmRt0D300EOuS3SD3r173zJHdpk2bZqGDx9uvXZzc9O33357x4NDqlSpoieeeMJ6HR8fr86dO9+xwblhw4Z0/42//fbbDE90BgAAAAAgJ7NYLIpLSrH7+cQUs15fuFtmsyXjhwE4xK4TQk6ePGlzXb16dZeEuVmNGjUkydp0O3XqlEvfd+jQIZvvNSkpSVeuXNGePXu0ZMkSm6akl5eXJk2apA4dOmQ47tdff60jR45o1apVklJPK65du7Z69uyptm3bqmTJkkpJSdGJEye0YsUK/fbbbzKbU/dN8PDw0Ndff62ePXsa/N0CAAAAAJC1BjQtq8U7zjp0iMi/4ZGas/mU+jctk/HDAOxmV1MwOjra+rmfn5/Llw6n8ff3l5+fn2JjY9PlcIXx48fr66+/vuMzJpNJnTp10ujRo1W3bl27xvX19dUff/yhDz/8UF988YWio6OVkJCgn376ST/99NMta9zc3HTvvffq/fffv+OehbeSkJCghIQESVJMTIxDtQAAAAAAuIqbm0kfP1hb949dq6QU+2f/jV6+Xx2qF1VooI8L0wH5i13Lh29cHpu2hDi/euihh/TGG2/Y3RBM4+HhoVGjRmnjxo1q3rx5hs/ff//9+t///udwQ1CSRo8eraCgIAUFBalTp04O1wMAAAAA4CqVQwM0rG0lh2qiE5I1asleFyUC8ie7moL+/v7Wz2NjYxUVFeWyQDeKjo62memWVTMU72TevHm666671Lp1ax05csTuukuXLmnw4MGqW7euzQEit7N06VLdfffdatasmQ4cOOBQxtdee03Xrl3TtWvXtGLFCodqAQAAAABwtRHtKqpiiJ9DNSv2ntPve8+5KJGTLuyXEmOzOwXgFLuagmXK2K7b37s3a7rzae9Jm51YunRpl77vq6++ksVisX7Exsbq1KlTWrp0qR5//HH5+vpan127dq0aN26sLVu2ZDju3r17VadOHU2dOlXJycmSpEaNGmnq1Kk6duyY4uLidP36de3fv1/jxo1TlSpVrLWbNm1SkyZNtHHjRru/D29vbwUGBiowMFB+fo79kAUAAAAAwNW8Pdz1cc86Dte9vWSPouKTXJDIQSlJ0prPpAmtpFUfZncawCl2NQVr1qwp6b9lxPPnz3ddohvMmzfP5rpWrVpZ8t40vr6+KlWqlDp37qwffvhBu3btUr169axfv3r1qrp3766rV6/edoyLFy+qY8eOioiIsN4bNWqU/v33Xw0aNEjly5eXj4+P/Pz8VK1aNQ0fPly7d+/Wo48+an0+OjpaXbt21YULF1zwXQIAAAAAkPUalyukAQ4eHnI+KkGf/ObYajrDndsjfd9eWvmBZE6SNoyTTm7K3kyAE+xqClasWFElSpSQlDprb9asWbp27ZpLg129elWzZs2yNiKLFSumihUruvSdGalUqZL+/PNPmxmLZ86c0WeffXbbmpdfflnnzv03vfnRRx/VO++8Y7NP4828vLz0ww8/qE2bNtZ7Fy9e1DvvvJO5bwAAAAAAgBzklfuqKTTQ26GaWZtOanN4pIsS3UFyorT6Y2lSG+ncrhu+YJGWjJCS4rI+E5AJdjUFJalnz56yWCwymUy6ePGiRo4c6cpcevHFF3Xx4kXrO3v27OnS99mrSJEievfdd23uTZ069ZbPXr58WbNmzbJeu7m56YMPPrDrPe7u7vrwQ9spyNOnT1diYqJjgQEAAAAAyKECfTz1blfHVwW+umCXEpJTXJDoNiJ2St+3k1aPlszJ6b9++bC06qOsywMYwO6m4NChQ62z2ywWi6ZMmaKvvvrKJaG+/PJLTZ482fo+k8mkoUOHuuRdzujRo4fNTL+zZ8/qxIkT6Z5bs2aNkpL+2+ugfv36KlmypN3vadGihQoXLmy9jomJ0datW51MDQAAAABAztOpVjF1qlnMoZqjF2M0ftVRFyW6QXJC6jLhSe2k83vu/OyGb6XTGZ87AOQUdjcFq1evrr59+1pn7lksFo0cOVJvvvmmUlKM6c6npKTojTfe0Isvvmh9h8lk0kMPPaQaNWoY8g4jBAcHq1ChQjb3blwinOb48eM21+XLl3foPSaTSWXLlrW5d+bMGYfGAAAAAAAgp3u3W00F+Hg4VDN+9REdPh/tokSSos5Kk9qmHihisaPvYTFLi4dLSfGuywQYyO6moJQ6g69IkSKSZG3ajR49WvXr19eqVasyFWTVqlWqV6+ePv74Y+tpw5JUsGBBffnll5kaOyt4enqmu5eQkGBz7eHh2A+4W41rVAMWAAAAAICcIjTQR6/eV82hmqQUi15duFtmsyXjh53hV1Ty8HGs5tJB6Z9PXJMHMJhDTcGiRYtq7ty51uZWWmNwz5496tixo6pXr65PP/1U27Zts1k2eyvJycnavn27Pv30U9WsWVMdO3bU3r17bWYienh4aPbs2SpWzLFpxK4WHR2tyEjbTU1DQ0PTPXfj0l8pdZmxo26eGRgSEuLwGAAAAAAA5HT9GpdRk3KFMn7wBltPXNGsTem38zKEu4fUbZzk7uVYXdjX0pltrskEGMjhqWvt2rXT3Llz1bdvXyUlJVkbeBaLRQcPHtRrr72m1157TZ6enqpWrZpCQkIUFBQkPz8/xcTE6Nq1a7p06ZIOHDhgPTTjxpmBNzYEZ82apbvvvtu479Ygy5Yts8kcEhKi4sWLp3uuXLlyNtf//vuvYmJi5OfnZ9d7Dh06pNOnT9vcq1ChguOBAQAAAADI4dzcTProwdq6/+u1Skwx2133yYqD6lgjVMWDfI0PFVpDavNy6r6C9rKkpJ5GPGS15OHYycpAVnJopmCa7t27a+XKlQoNDbXO7Ev7SGsQJiYmateuXVq5cqUWLVqkmTNnatGiRVq5cqV27typhIQE67M31xctWlR//vmnHnroIaO/30yLi4vTqFGjbO498MADcnNL/5/yrrvukrf3fz8A4uPj9e2339r9rtGjR9tcV6xYMV2jEQAAAACAvKJSUX893b6SQzXXE5L11uK9NpN3DNXyeal4XcdqLuyT1nzukjiAUZxqCkqpJ+Pu27dPjz/+uNzc3Kz/x3djg+/GJuGNHzc/I8l6f9CgQdq7d6/atGljzHd4Gy+//LI2b97sUE1kZKS6du2qQ4cOWe+5u7vrhRdeuOXzBQoUUI8ePWzuvf322/rrr78yfNd3332nqVOn2twbNGiQQ3kBAAAAAMhthrapqCqh/g7V/LX/vH7bk/4AUEO4e0rdxktu6c8SuKO1X0gRO12TCTCA001BKfUU3u+//1779u3TsGHDFBQUZNP8k9I3CW9sAqZ9BAYGasiQIdq9e7emTJmSbi8+V/jjjz/UpEkTNW3aVGPGjNGOHTtuuQ+ixWLRgQMH9P7776tq1arpGnovvPCCateufdv3vPfee/Ly+m//gcTERHXq1EkjR45MdzqxJO3cuVP9+/fX8OHDbe4XK1ZMzz//vIPfJQAAAAAAuYuXh5tGP1hH/98+sNuoX/bqWuydzzdwWrFaUuuXHKuxpEiLR0jJia7JBGSSyWLg/Nrk5GSFhYXpn3/+0Y4dO3T06FFFREQoOjpaiYmJ8vLykr+/v4oXL66KFSuqXr16atWqlVq1anXL03tdqV69etq507Zj7+XlpZIlSyo4OFheXl6Kjo7WqVOnFB196yPOBw0apMmTJ99y6fCN5syZo/79+99yKnPJkiVVvHhxpaSk6NSpU7p06VK6Z3x9fbV69Wo1adLEge8w1bp169SqVSvr9dq1a3XXXXc5PA4AAAAAAFnp7SV7NH2DY4eI9GtSWqMfrOOaQClJ0qR20vndjtW1fU1q+6prMgE3cLQH5PBBI3fi4eGhNm3auHzpr6skJibecvbezQIDA/Xxxx9r6NCh1pmPd9K3b195e3vrySef1OXLl22+dubMmXQnDN+oUqVKmjlzplMNQQAAAAAAcquX7q2qP/edV8S1eLtrZv97St3qlVSzCi5YgejuKXUfJ33fXjIn21+35jOpWmep2O1XGQLZIVPLh3Oz2bNn65NPPlHHjh0VGBiY4fMmk0l16tTRZ599piNHjmjYsGF2NQTT9OjRQ/v379e7776rMmXKZPh8jRo1NHbsWO3YsUNNmza1+z0AAAAAAOQFAT6eer9bLYfrXl+4W/FJKS5IpNQDR+76n2M15mRp8fDUmYZADmLo8uHcymw26/Dhwzpy5IhOnjypqKgoJSUlKSAgQEFBQSpXrpwaNGhgV/PQXidOnNDWrVt1/vx5Xbt2TSaTScHBwSpRooSaNGmi0NBQQ97D8mEAAAAAQG42YtY2Ldsd4VDN0+0q6cV7q7omUHKiNKlN6gnDjmj/puP7EgIOyNblw7mVm5ubqlatqqpVXfQD4xbKli2rsmXLZtn7AAAAAADIjUZ1raG1hy8qKt7+JbsT/jmqB+oWV7Vixk3usfLwkrqNk37omHqYiL1WfyJV7SyF1jA+E+CEfLt8GAAAAAAA5HxFA3z0+v3VHapJNlv06oLdSjG7aHFkyQZSy+ccqzEnSUuGSykO7EcIuBBNQQAAAAAAkKP1aVxazSoUcqhmx6mrmrEh3DWBpNQThUOqOVZzdru04RvX5AEcZPfy4ZMnT7oyh13sOaADAAAAAADkLSaTSaMfrKN7v1qjxGSz3XWf/n5Qd9csppLBvsaH8vCWuo2XfuwoWezPpFUfSVXvl0Kybgsz4FbsbgqWK1fOodN2jWYymZSczBTb3MhischsNislJUVmswM/KAEAOYKbm5s8PDzk5sYCAwAAkH3KF/HTcx0q67PfD9pdE5uYorcW79GPgxq5pqdRqqHU4hkp7Gv7a1ISU08jfvwPyc3d+EyAnRw6aISDimEvi8WihIQERUVFWU9zBgDkbgUKFFBQUJACAgLk7s7/gAUAAFlvSOsK+nXnWR04F213zcoDF7R0V4S61C3hmlBtX5cOLJcuH7a/5swWacM4qeWzrskE2MGhpmB2zRSkGZm7xMbGKiIiQomJiXJ3d1dAQID8/Pzk7u4uNze3bJ1xCgBwTNps76SkJEVFRSkiIkLnzp1T4cKFFRISkt3xAABAPuPp7qaPe9ZRj/FhcqRV8O6ve9WqchEFF/ByQSif1NOIJ98ryYFQqz6Uqt4nFalsfCbADswUhKFiY2N16tQpeXt7q3Tp0vLz86MJCAB5RHBwsJKSknTlyhVdunRJbm5uKly4cHbHAgAA+Uy90sF6tEU5TQkLt7smMiZR645c0gN1XDRbsExTqfkIacO39tckx0tLRkiDf2MZMbKF3U3BVatWOTy4xWJR+/btrU2hF154QV26dHF4HOQOaQ1BHx8flS5dmr2nACAP8vT0VNGiRSVJFy5ckIeHh4KCgrI5FQAAyG9evKeq/th7XmeuxmX4bI3igfq4Z23VKRXs2lDt3pAOLpcij9lfc2qTtGmi1Hy463IBt2F3U7BNmzaZflmVKlUMGQc5j8ViUUREhHWGIA1BAMjbQkJClJycrIiICAUEBPBzHwAAZCk/bw990L2WBk/dfNtnvD3c9MLdVfT4XeXl6Z4F/1vFq0DqMuIp98uhZcR/vydVuVcqXNFl0YBb4X/BwxAJCQlKTExUkSJF+MUQAPIBk8mkwoULy2KxKDY2NrvjAACAfKhdtaK3PTykRcXC+v351hrapmLWNATTlG0hNX3KsZrkOOmXZySz2TWZgNugewNDREVFyd3dXX5+ftkdBQCQRby8vOTp6anr169ndxQAAJBPjepSQ8EFPK3XQb6e+qxXHc16oqnKFcmm3087vC0VLOdYzYkwafMPLokD3A5NQWSaxWJRVFSUAgICOFQEAPIRk8kkf39/RUdHcxgZAADIFkX8vfXG/dUlSV3rltDfI9vooUals/d3Uy8/qasDB46k+WuUFHnc+DzAbdAURKaZzWYlJSUxSxAA8qECBQooOTlZZpa7AACAbNKrYSnNH9pcY/vVVxF/7+yOk6p8K6nxk47VJMWyjBhZiqYgMi0lJUWS5O7OEeoAkN+k/exP+7cAAAAgq5lMJjUqVyi7Y6TX8R0puIxjNeFrpa2TXRIHuBlNQWRa2uwQDhgBgPwn7Wc/MwUBAABu4u3v3DLiP0dJV04Ynwe4CV0cGIb9BAEg/+FnPwAAwB1UaCM1HOxYTeJ16ddnJfZshovRFAQAAAAAAHCVu9+TAks5VnNstbRztkviAGloCgIAAAAAALiKT6DUdaxjNQ0flao94JI4QBqaggAAAAAAAK5UqYNU/5GMnwsqIz2yWOrydWozEXAhmoIAAAAAAACudu+HUmDJ23+98RPS8PVSxXZZlwn5Gk1BAAAAAAAAV/MJSp0BeLPgstKgX6XOX0jeAVmfC/kWTUEAAAAAAABJxy/F6ND5aNe9oPLdUr0B/103HSoN3yCVb+26dwK34ZHdAQAAAAAAALJTUopZ3689pq//OqxKRf21ZERLebi7aB7VvR9KV05I7d+QyrZwzTsAO9jdFGzfvn2mXzZmzBjNmTPHqVqTyaS///470xkAAAAAAADS7Dx1Va8u3K39EVGSpL1no/TjuuN6qk1F17zQt6A0eJlrxgYcYHdTcPXq1TKZTE69xGKxSJIOHz6sw4cPO1Xv7LsBAAAAAABuFpOQrC/+OKSp64/LbLH92pd/HdJ9tYqrTOEC2RMOyAIu31PQZDJZPwAA9nnnnXdsfn6WK1cuuyPdVtofjW78CA8Pz+5YAAAAwG2tPnhB93y5RpPD0jcEJSk+yazXF+22TnIC8iKH9hTk/xgAAAAAAEBudfl6gt5fuk+Ld5zN8Nl1Ry5p4bYz6tmwVBYkA7Ke3U3BQYMGuTIHgFxm9erVateu3S2/5uXlpXPnzqlgwYKZeseRI0dUuXLl2379+PHjOXoGHQAAAICcIyYhWfd+tVaXrifYXfP+sn1qUzVERfy9XZgMyB52NwWnTJniyhwA8pDExETNmTNHw4YNy9Q406ZNMygRAAAAgPzOz9tDPRuW1MR/jtldczU2Se8v3aev+9Z3YTIge7h8T0EA+VNmG3oWi0UzZswwKA0AAAAASM93qKIyhRw7PGTJjrNadfCCixIB2YemIACX2LRpkw4dOuR0/apVq3TixAkDEwEAAADI73y93PVRj9oO1725aI9iEpJdkAjIPjQFARjm5j0EMzNb8ObazO5PCAAAAACSdFflIurZwLHDQ85cjdMXfzg/6cFlLBbp6qnsToFciqYgAMP06dPH5nrmzJlOnVp+/fp1LViwwHrt5uam3r17ZzofAAAAAEjSm52rq7Cfl0M1U9cf185TV10TyBlRZ6Wfekvft5NiLmd3GuRCNAUBGKZly5aqVKmS9frkyZNatWqVw+PMnz9fMTEx1uv27durVCnH/pIHAAAAALdT0M9Lb3ep4VCN2SK9smCXklLMLkplJ4tF2j5TGtdMOvyHFHNR+u3l7M2EXImmIABDDRw40ObamSXEN9cMGjQoU5kAAAAA4GZd65ZQ26ohDtUcOBet79faf3qx4a6dlmb2lJaMkBKu/Xd/z3xp/9Lsy4VcySO7AwDIWx555BGNGjXKumx4wYIFGj9+vPz8/OyqP3HihP755x/rdUBAgB588EGNGTPG0Jzh4eHauXOnLly4oEuXLsnf319FixZV+fLl1bBhQ7m7uxv6PknavXu39u3bpzNnzigxMVGFCxdWjRo11KRJE3l6ehr+vptFRERo27ZtunDhgi5evCh3d3cVLVpUpUuXVrNmzeTj4+PyDAAAAEBOYTKZ9EH3WrrnyzWKTUyxu+7rvw7rvlrFVb6Ifb/jGMJikbZNk35/U0qMvvUzS1+QyraQChTKulzI1WgKAjBUuXLl1KZNG61evVqSFBMTowULFqSbQXg706dPt9mHsFevXipQoIAh2aKjozVmzBjNmzdP+/btu+1zhQoV0v33369XX31VNWvWzNQ7U1JS9O2332rChAk6cODALZ8JCgrS448/rtdff12FCxfO1PtuFhUVpa+//loLFy7Ujh07bvucr6+v2rVrp1dffVWtWrUyNAMAAACQU5UqWEAj76mq95fe/veDmyUkm/X6wt366cmmMplMLkz3/66ckH59Vjq2+s7PxVyQVrwmPTjR9ZmQJ7B8GIDhbl7u68gSYlctHZ45c6YqV66sd955544NQUmKjIzUzJkzVbduXQ0dOlRxcXFOvfPw4cNq1qyZnn/++ds2BCXp2rVrGjNmjGrWrKm1a9c69a5b+fbbb1WxYkW9/fbbd2wISlJcXJyWL1+u1q1bq1u3brpy5YphOQAAAICc7NEW5VS3VJBDNRuOXdbPW067KNENts+SvmuRcUMwza450sEVLo2EvIOmIADD9erVy2a58OrVq3Xq1KkM69atW6ejR49ar8uVK6fWrVtnOs8HH3ygRx55ROfPn3eoLiUlRRMnTtTdd9/tcJPs6NGjatu2rbZs2WJ3zfnz53XPPfdow4YNDr3rZklJSXr00Uf1zDPP6NKlSw7X//LLL2rRooXCw8MzlQMAAADIDdzdTPq4Zx15uDk26+/D5ft1MTrBRan+n8kkJV53rGbp81Icf+RHxlg+DMBw/v7+6tGjh2bOnClJMpvNmjFjhl5//fU71t08S/CRRx7J9HT8zz//XG+99Va6+76+vurcubNatmyp4sWLKyoqSgcOHND8+fN18uRJm2fDwsJ07733KiwszK69/6KiotSxY0edPXs23dfq16+vbt26qVy5cnJ3d9fJkye1bNkybdiwQRaLRfHx8erZs6d6/qwM7QAAmhlJREFU9+7t1PdrsVjUq1cv/fLLL+m+VrlyZbVv31516tRRoUKFZDabFRERobCwMC1fvlwJCf/9D5oDBw6oS5cu+vfff+Xr6+tUFgAAACC3qF48UENaV9D41Uczfvj/XYtL0ru/7tW3/Ru4LljdftLeRamnDNsrOkL6/Q2p+3jX5UKeQFMQgEsMGjTI2hSUUvcKvFNTMC4uTvPmzbO5Z+8+hLezc+dOvfHGG+nud+vWTRMmTFCxYsXSfe2zzz7TmDFj9Oabb9o0yTZv3qx33nlHH374YYbvfe2119LNsgsNDdX333+vLl26pHv+9ddf19q1azVo0CAdP35cERERmjjRuX1APvvss3QNwSpVqmjs2LG69957b1kzcuRInT17Vs8//7x+/vln6/09e/boueee06RJk5zKAgAAAOQmz3aorOW7IxR+OdbumqW7ItSj/nl1qB7qmlAmk/TAV9L4ZlJClP11O2ZJNXtIle92TS7kCSwfBuAS7du3V6lSpazXBw8e1KZNm277/KJFixQV9d8/ci1btlSlSpUylWHo0KFKTEy0uTdw4EAtWrTolg1BSXJzc9OLL76oOXPmpDuB+JNPPtHBgwfv+M4dO3bou+++s7lXqFAhrVy58pYNwTStWrXS2rVrVaZMGUlSfHz8Hd9zK3v37tWbb75pc69Dhw7avn37bRuCaUqUKKF58+bpmWeesbn/448/2izpBgAAAPIqH093ffRgbYfr3ly8R9cTkl2Q6P8FlZTu/cjxul+eleKvGZ8HeQZNQQAu4ebmpkceecTm3p0OHDH6gJF///1XGzdutLlXvXp1/fDDD3YtSe7evbteeeUVm3tpJwnfyXfffWdzerIkTZgwQTVq1MjwnSVLltTs2bOdXjL96aefKikpyXpdrlw5LVmyxKHTm7/88kvVrVvXem02mzVmzBin8gAAAAC5TYuKRdSnUWmHaiKuxevz3+88eSDT6j8sVezgWE30WemPNzN+DvkWTUEALnNzY2/OnDnpZu5J0pkzZ/TXX39Zr318fJzeUy/NhAkT0t374osv7NoTMM0bb7yRbkbhtGnTFBt76+UEMTExmj17ts29Fi1a6KGHHrL7nY4+n+bs2bPp3j169GibA1/s4e7unq4Zeqv9CQEAAIC86vX7q6uIv7dDNdM2hGvbSRce7mEySV2+lrwCHKvbNl068rdrMiHXoykIwGWqVq2qpk2bWq+vXLmiX3/9Nd1zM2bMkNlstl53795dQUFBmXr3jU1GSSpdurQ6derk0BgFChTQww8/bHMvOjpa//777y2f37Bhg6Kjo23uPf744w6909mapUuX2swSDAwMVI8ePRweR1K6/06nT5/WsWPHnBoLAAAAyG2CCnjqna4Zr/S5kcUivbZgtxKTzRk/7Kzg0tI97zte9+tzUkJ0xs8h36EpCMClbp4teKslxEYvHT579qxOnTplc69bt25OLcvt1atXunsbNmy45bO3ahZ27drV4Xd26NBBAQGO/QVw7dq1NtcNGjSQt7djf91MU7BgQQUHB9vc27Fjh1NjAQAAALlR59rF1aFaUYdqDp6P1sR/XLwfd8NHpQptHau5dkr6821XpEEux+nDAFyqb9++euGFF6wn+f7222+6ePGiQkJCJKU20g4cOGB9vnjx4rr77sydkLV9+/Z09xo2bOjUWHXr1pWHh4eSk//bOPhW49/qfunSpVWkSBGH3+nu7q46deooLCzM7pr169fbXO/cuVP16tVz+N1pYmJibK4vX77s9FgAAABAbmMymfR+91raOOYfxSSm2F33zcojur9OcVUM8XdVMKnLWGl8cykpJuPn02yZLNXoLlVo45pcyJVoCgJwqYIFC6pLly6aP3++JCk5OVk//fSTnnvuOUnS1KlTbZ5/+OGH053666hLly6lu1e1alWnxvLx8VG5cuV05MiRO44vSRcvXrS5rlKlilPvlFLzOtIUPHv2rM31lStXdOWKcXua0BQEAABAflMi2Fcvd6qmUb/stbsmMcWs1xbu1pwnm8nNzbkDBDNUsKx097vS8hcdq/vlaWnYBsnbRQ1L5DosHwbgcgMHDrS5TlsunJCQoDlz5tzxWWfcqhmWmT0Kb15Ke/Xq1Vs+d/P9zLwzMDDQ7mdjY2MVHx/v9Lvs4erxAQAAgJzo4WZlVb9MsEM1/x6P1NwtpzJ+MDMaPS6Va+VYzdWT0l/vuCQOcieaggBc7r777lPRov/tx7F9+3bt2bNHv/76q00Dr0GDBqpVq1am33f9+vV09xw9hfdOtTcfJnK79xYoUMCwd97J7ZqUAAAAADLH3c2kjx+sI093x2b9fbR8vy5EufAP625uUtdvJE8Hf+fY/L0Uvs41mZDr0BQE4HIeHh7q37+/zb1p06YZfsBIGn//9NPhb94jzxE3197uEJCb3xsbG2vYO+/E19c33b0+ffrIYrEY9vHOO+84/b0AAAAAuVnVYgEa1qaiQzXR8ckOLTt2SqHyUsd3HK9bMkJKdP73I+QdNAUBZImbG35Tp07VihUrrNeenp7pGofOKliwYLp7165dc3q8m2fi3byc+Hb3M/POqKgou58NDg5Otw9jZGSk0+8GAAAAYGt4u0qqEOLY6qPf9pzTH3vPuSjR/2v8pFSmhWM1V8Klv993SRzkLjQFAWSJevXqqU6dOtbrS5cu2Zzoe//99zt1Uu+t3GqcgwcPOjVWQkKCwsPDMxxfkvVE5TSHDh1y6p2SY3lNJlO6TCdPnnT63QAAAABs+Xi66+MH62T84E3eWrJHUfFJLkj0/9zcpG7fSh7pVw/d0aYJ0okNrsmEXIOmIIAsc6flwUYtHZak+vXrp7u3detWp8bauXOnTfNSSt370J73njp16rYnFd+J2WzWrl27HKpp3LixzfWhQ4ecejcAAACAW2tSvpD6NSnjUM35qAR9uuKAixL9v8IVpQ5vOVhk+f9lxM5veYTcj6YggCwzYMAAeXh4pLtfuHBhde7c2bD3lChRQmXK2P5j/csvv8hisTg81oIFC9Lda968+S2fbdKkSbp7v/zyi8Pv/Pvvv297mMnttG/f3ubaYrFoyZIlDr8bAAAAwO29el81FQ3wdqhm5saT2hLu4u19mg6VSjd1rCbyqLTqQ9fkQa5AUxBAlgkNDdW9996b7n6/fv3k5eVl6Ls6duxoc33y5EmbPQztERcXp5kzZ9rcCwwMvGXzT0ptFt58CMmUKVMceqckTZ482eGazp07y2SyPRHtiy++kNlsdngsAAAAALcW5Oup97rVdLju1YW7lZCc4oJE/8/NXeo2TvLwcaxuwzjp1L+uyYQcj6YggCw1Z84cRURE2Hx8+umnhr9n6NCh6e6NHDlSSUn27+cxevRonT171ubeoEGDbnnaryT5+fmpX79+NvfWrVt3y9mGt7Nx40bNnTvX7ufTVKlSRQ8++KDNvf379+vdd991eCwAAAAAt9epVnHdUyPUoZq6pYKVmOziP9gXqSy1e8PBIou0eLiUFOeSSMjZaAoCyFL+/v4qVqyYzcftmmyZ0bhx43TLfPfv368nn3zSrmXEv/zyi0aPHm1zz93dXU8//fQd64YNG5Zuxt7QoUPtOjjk7Nmz6tevn1PLnCXp7bffTncK8fvvv69vvvnGqfFiY2P19ddfOzXbEQAAAMjL3utWSwHe6bdGulmZQgU08/Gm+qJ3XQX4eLo+WPMRUslGjtVcPiytHp3xc8hzaAoCyLMmTJiQblnytGnT1LNnT50/f/6WNWazWV9++aX69OmT7oCRV199VVWqVLnjO+vVq5duluKlS5fUtm1bLVu27LZ1YWFhat26tfWkYx8fB6f9S6pTp44++ugjm3sWi0XPPvusevbsqT179tg1zsaNG/X888+rXLlyev7553XmzBmHswAAAAB5WbEgH718X7Xbft3dzaSnWlfQ78+31l2Vi2RdsLRlxO4Obs+0/hvptHOHMyL3yritDQC5VFqT7MUXX7S5v2jRIq1YsUJdunRRy5YtFRoaqujoaB04cEDz58/XiRMn0o3VuHFjjRo1yq73fvzxx/rtt9+sDT5JOnfunB544AE1bNhQ3bp1U9myZeXu7q5Tp05p2bJlCgsLs84QLFasmHr37q2xY8c6/D2//PLL2rFjh2bPnm1zf+HChVq0aJEaNGigtm3bqmLFiipUqJBSUlJ09epVRUREaNu2bdqyZYsuXLjg8HsBAACA/GZAkzJasv2Mtpy4YnO/VslAffxgHdUqGZQ9wYpWk9q+Jv3twFZCFrO0ZLj01BrJw7GDVJB70RQEkKeNHDlSMTEx6Rp6cXFxmjdvnubNm5fhGC1atNDSpUvl6WnfdP/AwED99ddfat26dbo9Cbdu3aqtW2//Fzhvb2/Nnz9ff/75p13vupUZM2aoVKlS+uyzz2zuWyyWDN8PAAAAwD5ubiZ93LO27v96nRJTzPLxdNPIu6tqcMty8nDP5oWZLZ6V9v8ind1uf83FA9I/n0gd3nZdLuQoLB8GkOe9/fbbmj59uooWLepQnbu7u4YMGaI///xTBQsWdKi2YsWKWrVqlRo2bGh3TZEiRbRixQq1bNnSoXfdzN3dXZ9++qkWLVqU4XLnjLRo0UJt27bN1BgAAABAXlWpaICGt6uoVpWL6I/n2+jJ1hWyvyEoSe4eUrfxkpuD+xiu+8qxRiJytRzw/1MBwPUeeeQRHTlyRO+8846qV69+x2cLFSqkAQMGaMeOHZo4caIKFCjg1DurVKmiTZs26csvv1TVqlVv+1xgYKCeeeYZ7d2719AGXPfu3bV//3799NNP6tSpk/z8/DKs8fb2Vrt27TR69GgdPHhQYWFhuuuuuwzLBAAAAOQ1T7erpOmPNVGZws793uAyoTWkNq84VmNJkRaPkJITXZMJOYrJ4uwxl8gV1q1bp1atWlmv165da/gv+PHx8Tp+/LjKly/v1OEIQHY4fvy4duzYoQsXLujy5cvy8/NT0aJFVb58eTVu3DjdKb5G2Llzp/bt26ezZ88qISFBhQsXVs2aNdWkSZN0B6K4QlJSkrZu3aqTJ0/q0qVLunLliry8vBQYGKjQ0FBVq1ZNlSpVkocHO0vAfvwbAAAAkIOlJEnft5fO7XKsrs0rUrvXXZMJLuNoD4jf/ADkS+XLl1f58uWz9J1169ZV3bp1s/SdN/L09FSzZs3UrFmzbMsAAAAAIAu5e0rdx0uT2krmZPvr1n4hVXtAKl7HZdGQ/Vg+DAAAAAAAkFcVqy21fsmxGnOytHh46kxD5Fk0BQEAAAAAAPKyu/4nhday/3nvIKnZMMmNBaZ5GU1BAAAAAACAvMzDS+o2TjLZsXd6lU7SiE1S/QGSyeT6bMg2NAUBAAAAAADyuhL1pFb/u/3XfYKlHpOkfnOkwOJZlQrZiKYgAAAAAABAftD6JSmkevr71R5InR1Ytw+zA/MRmoIAAAAAAAD5gYd36mnEacuIfQtJPX+U+syUAoplbzZkOZqCAAAAAAAA2exCVLz+N3eHzl6Nc+2LSjaQWj4r1eiWOjuwdi9mB+ZTHCMDAAAAAACQTcxmi+ZuOaWPlu9XdHyyrsUl6YdBjWRyZaOu/VuSmx2HjiBPoykIAAAAAACQDY5evK7XFu7Wv8cjrff+PnBBy3ZH6IE6JVz3YhqCEE1BAAAAAACALJWYbNakNUc1duURJSab0339nV/2qVWlEAUV8MyGdMgv2FMQAAAAAAAgi2w/eUVdvlmnz/84dMuGoCRdup6gj5bvz+JkyG+YKQgAAAAAAOBi1xOS9fnvBzVtQ7gsloyfn7vllLrVL6EWFYu4PhzyJWYKAgAAAAAAuNiW8EhNXW9fQzDN6wt3Kz4pxXWhkK/RFAQAAAAAAHCxtlWL6oE6xR2qCb8cq7F/H3ZRIuR3NAUBAAAAAACywKguNRXk69jhIZPWHNP+iCgXJUJ+RlMQAAAAAAAgC4QEeOuNztUdqkk2W/Tqgl1KMTuw7jgrJVyXzLc+MAU5G01BAAAAAACALPJQw1JqUbGwQzU7T1/T1PXhrgmUGUdXSuObSZt/yO4kcAJNQQAAAAAAgCxiMpn0UY/a8vZwrCXzxR8HdfpKrItSOSj+mvTLM9KMHtK1U9Jf70hXwrM7FRxEUxAAAAAAACALlSvip+c6VnaoJjYxRW8u3iOLI8cXu8Lhv6TxzaVt0/+7lxQjLXmaZcS5DE1BAAAAAACALPZkqwqqXjzQoZrVBy/ql51nXZQoA3FXpcUjpFk9pagz6b8evlbaOiXLY8F5NAUBAAAAAACymKe7mz7pWVv/1959xzV19X8A/4SwZG8VUVFwICgq4rZq3XtVax3VVq1aV63aWuveto62T23Vaq2j9alb69a66h51g6iouGWI7Jnc3x/84OEmAXJDQgJ83q8Xr/ae3HPON5cDwpczzGTS6s39KwSxSemGCSovYYey9g68vjn/+47OBN4+KZqYqNCYFCQiIiIiIiIiMoI6Xk74qFkVSXViktIxf3+ogSJSkfIW2DkS2PI+kPCy4PvTE4G94wFjL3EmrTApSERERERERERkJJ+3q44KTmUk1dnx7zOcuR9toIhykZkBj89Iq/PwhHi/QTJZTAoSERERERERERmJrZU5FvQKkFxv2q5bSElXGCCiXKwdgO7fS693+Gsg7pn+4yG9YlKQiIiIiIiIiMiIWtXwQM+6npLqPHmTjO/+vmegiHLxbQvUGyStTnoC8NcELiM2cUwKEhEREREREREZ2YyuteBsYyGpztp/HuH28zgDRZRL+wWAvbSkJR4cA67/bph4SC+YFCQiIiIiIiIiMjJXOytM71JLUh2FUsDUnTeRqVAaKKr/V8YJ6KbDMuJD04D4F3oPh/SDSUEiIiIiIiIiIhPQu34FtKjmJqnO7efxWH/2sWECyq16eyBwgLQ6aXHAX59xGbGJYlKQiIiIiIiIiMgEyGQyLOhZG9YW0tI1y46G4UlMsoGiyqXjQsCunLQ69w8DN/80TDxUKEwKEhERERERERGZiEquNvi8XXVJdVIzlPh69y0Ihp6RV8YZ6Pad9HoHvwQSXuk9HCocJgWJiIiIiIiIiEzIx82qIKCCg6Q6/9yPxq5rzw0UUS41OgG1+0mrk/oW2Pc5lxGbGCYFiYiIiIiIiIhMiLncDIt714HcTCap3rx9IYhJTDNQVLl0WgLYekirE7YfuL3DMPGQTpgUJCIqJmQymejjt99+M3ZIRERERERkIAEVHDG8eRVJdWKTMzB/f6iBIsrFxgXoulx6vQOTgcRI/cdDOmFSkIiIiIiIiIjIBH3WtjoqudhIqrPr2nOcuhdloIhy8esG+PeWViclFtjPZcSmgklBIiIyuLS0NFy6dAk//fQTPvroIwQEBEAul6vNfnz8+LHe+05KSsKZM2ewYsUKDBgwANWrV4eZmZla30REREREpqaMpRwLegVIrvf1rltITs80QEQqOn8L2LhJqxP6F3Bnl2HiIUnMjR0AERGVPImJifjzzz9x+fJlXL58Gbdu3UJGRkaR9B0ZGYnt27fj8uXLuHLlCkJDQ6FQKIqkbyIiIiIifWtRzR2961fAzn+1P0TkWWwKlh+5h+ldaxkwMgC2bkCXpcC2odLqHZgMVHknqz4ZDZOCRESkdw8ePMDw4cON0ve5c+cwZswYo/RNRERERGQIM7rUwqmwKMQkpWtd59ezj9C9rifqeDkZLjAA8O+VNfMvZI/2dZJjshKDfX8zWFhUMC4fJiIiIiIiIiIyYc62lpjZTdqsP6UATN1xCxkKpYGiyqXzMqCMi7Q6d3YBIXsNEw9phUlBIiIqMjKZDL6+vvjggw8QGBhYpH2bmZnB398fQ4YMgbe3d5H2TURERERUWN0DPdGyurukOiEv47H2n0cGiigXO/es/QWl2v85kPxG//GQVrh8mIiIDMbLywvBwcEIDg5GgwYN0KBBAzg7OwMAhg4dihs3bhisbx8fn5x+g4ODUb9+fdjZ2QEAWrVqZZBDTYiIiIiIDEUmk2F+zwC0X3EaKRna75n93bF76BRQDt5utgaMDkBAn6zZf3f3aV8nKQo4+AXQZ63h4qI8MSlIRER6V716dbx8+RLlypUr8r5btWqFmJgYuLhIXL5ARERERGTiKrrYYFL76pi/P1TrOmmZSszfH4q1QxoYMDIAMhnQZTnw+AyQ+lb7ere2Ze1LWLOLwUIjzbh8mIiI9M7GxsYoCUEAcHJyYkKQiIiIiEqsj5pVQaCXo9b3t6npgbk9/A0YUS72ZYFO30ivt28ilxEbAWcKEhHp0d27dxESEoLIyEi8efMGTk5O8PDwQLVq1Yp8D72CPH78GDdu3EBkZCSio6NhZ2cHDw8PVKlSBUFBQZDL5cYOsUR69eoVLl68iEePHiExMRH29vaoUaMGmjVrBnt7e63aSE5OxqVLlxAaGorY2FjY2trC09MT77zzDsqWLWvgd0BERERExiQ3k2FR7zro9uMZKJRCnve52VliVjd/dK1THjKZrOgCrNMvaxnxvYPa10l8DRyeBvRaZbi4SA2TgkR6kqFQ4vjdSIRHJSI5TQEbKzl83O3wbk0PWMg5KVffdu/ejV69eonK9uzZg+7du+vc5pIlSzB16lRRWUhICPz8/PKtFxkZiW+++QY7d+7Eo0d5b+Lr6emJ7t27Y+rUqahcubLOcRZGQkICli9fjq1btyIkJCTP+1xcXNC5c2dMnToV/v5F9FfFYu63337DRx99JCoThP/9kHby5EnMnTsXJ0+eFJVns7GxwUcffYR58+bl7LuoKiIiAvPmzcN///tfJCUlqb1uZmaGNm3aYMWKFfy8EREREZVgtTwd8Mk7VfHzyXCNr/dr4IVpnf3gZGNZxJEhaxlx1xXAT+eA1Djt693YkrWMuHoHw8VGIsxUEBXS6/hULD96D40W/o2Rm65i2ZF7WHUqHMuO3MPITVfRaOHfWH70Hl7Hpxo71BKlW7du8PLyEpWtWbNG5/YEQcDateLNbVu0aFFgQnD58uWoVq0ali1blm9CEABevHiBVatWoWbNmpg+fToUCu03B9aHzZs3o1q1apg9e3a+CUEAePPmDTZv3ozAwECMGjUKKSkpRRRlyaNQKDBhwgS0bt0aJ06c0JgQBLJm/61cuRJ169ZFaKj6HjF//PEH/P39sW7dOo0JQQBQKpU4evQo6tWrh61bt+r1fRARERGRaZnQphq8XW1EZd6uNvhjRCN8816gcRKC2RzKAx0WSa/31wQg5a3ewyHNmBQkKoTz4TF4d+lJ/Hj8Pt4kpQMAFEoBmUohZxr3m6R0/Hj8Pt5dehLnw2OMGW6JIpfLMWLECFHZoUOH8PTpU53aO378OB48eCAq++STT/K8X6lUYuTIkZg0aRLi4+Ml9ZWamooFCxagb9++SEtL0yleqebPn4/Bgwfj9evXkuopFAqsXr0a7dq1Q2xsrIGiK9mGDh2KH374Qev7nzx5gg4dOiAyMjKnbNWqVRg0aFCeyUBVGRkZGDhwIE6cOCE5XiIiIiIqHqwt5FjYuzaArCXFn7bywaHP3kFTHzcjR/b/6g4AfNtJq5PwEjj8tWHiITVcPkwmJy1TgfRMpbHDyJeF3AzXnrzF4HUXoRQE5LONAwBAKQApGQoMXncRm4Y1QhMfVwBAaoYCGQrTfK+W5mawMjftPeWGDx+OefPmITMzE0BWAmvdunWYPXu25LZUZxm6uLjgvffey/P+8ePHa5yZ6OjoiJ49eyIoKAgeHh548+YNbt26he3btyMqKkp0765du9C/f3/s2rVLcrxSLF26FDNmzFArL1OmDLp06YJmzZqhfPnyiI+Px927d7F9+3Y8efJEdO/Zs2fRoUMHnD17FhYWFgaNtyRZtmwZNm/enHPt5+eH7t27o1q1arC3t8erV69w7Ngx7Nu3TzSD8OnTp5g0aRI2bdqEEydOYOzYsTmvly1bFt26dUO9evXg5uaG+Ph4XLhwAX/++ScSExNz2sjMzMSoUaNw8+ZNWFlZFd2bJiIiIqIi09THDV92rImW1d1Ry9PB2OGIyWRAt++BnxoDaRImUlzfnLWMuFpbw8VGAJgUJBP004lwfP/3fWOHka/udTzx993XWiUEs2XdJ2D4xss4PqkVyjpYY9aeO/jzim4z2wxtQptqmNiuurHDyFf2Hn07d+7MKfv1118xY8YMSYdkREVFYffu3aKywYMHw9raWuP9Bw4cwMqVK9XKR4wYgaVLl8LBQf0f4xUrVmDmzJn49ttvRcmf3bt345dfflGb9agvN27cwNdfq/+lrUePHli1apXGE4K//fZbLF++HNOnTxfNZLx8+TJmz56NBQsWGCTWkij72Ts5OeHnn39G//791e4ZP348zp49i65du+Lt27c55b///js+//xzfPjhh1AoFDAzM8OMGTPw5ZdfokyZMqI2hg8fjtmzZ6NLly64efNmTvm9e/fwxx9/qO11SEREREQlx+hWPsYOIW+OFYAOC4C946TV+2s88Ol5wFr7U5ZJOi4fJtJBeFQiUjIUWicEsykFICVdgT8uPin4ZtLK6NGjRddPnz7FwYMSTrlC1gER6enporK8lg5nZmZi5MiRauXTp0/HmjVrNCYEAcDKygpLlizB999/r/ba559/brCluaNGjVJ7bx9++CF27dqlMSEIZB1WMXnyZPz3v/9VS64uWbIEYWFhBom1JEpLS4OTkxNOnTqlMSGYrVmzZtiwYYOoTBAEdOjQAc+ePQMAbNq0CbNnz1ZLCGbz8vLC/v37YWMj3ldGtV0iIiIioiJVbzDg8660OvHPgSPqq51Iv5gUJNLBg6hEyQnBbEoB2HwhwmSXDRc3bdq0QbVq1URlUg8c+eWXX0TXzZo1Q61atTTeu3PnzpwkTba2bdti3rx5WvU1btw4DBgwQFSWmJiIX3/9VULE2rl06RIuXLggKvPz88PatWshk8kKrN+zZ098+eWXojKFQoEff/xRr3GWdCtXrkSdOnUKvK979+6oW7euqCx7yfmoUaPUxo0mXl5eGD58uKjszJkzPCiGiIiIiIxHJgO6/QBY2kur9+8GIJx7ZBsSk4JEOkgr5J6HMUnpOHE3suAbqUAymQyjRo0SlR04cADPnz/Xqv7Jkydx/754ubqmmYDZVq1apVamafZffpYuXaq2x9tPP/0kqQ1taIp12bJlkvYE/Prrr9VmFG7YsAHJycmFjq80CAgI0CqZl61Xr15qZRYWFpg1a5bWbfTu3Vt0rVAoREuKiYiIiIiKnFNFoP1caXXKBwJ2ZQ0TDwFgUpBIJwXPscqf3EyG8CjtThGlgg0dOlS0/59CodB65p3qrEJnZ2f07dtX472pqak4c+aMqCy/WYV5KV++PLp16yYqe/jwIR4/fiypnYIcO3ZMdF2xYkV07NhRUhs2NjYYNGiQqCwhIQGXLl0qdHylwZAhQyTdHxgYqFbWoUOHPJd6a9vGvXv3JMVBRERERKR3QR8BVd4p+D65JfDuDGD430BZab9rkTRMChLpopBZQRmApLRMvYRCWScF9+vXT1S2bt06KJX5z+iMiYkRHVIC5H/AyNWrV5GRkSEq0zSzSxuaTjY+f/68Tm1p8uLFCzx9Kj7EpkePHlotG1Zl6FhLsubNm0u6v1KlSmplzZo1k9SGk5OT2t6WcXFxktogIiIiItI7mQzo/iNgYZv3PRWCgJGngXcmA3LtVziRbpgUJNKFjvsJ5q5ua8XDv/VJ9cCRiIgIHD58ON86GzZsEJ2uC+R9wAgAXL9+Xa0sKChI+yALqHft2jWd2tJEU1u6xhoYGAhzc/F41WesJZmPj7ST4Ozs7ArdhqZ2mBQkIiIiIpPgXBloN0e9XG4FtJ0DfHwE8PAr+rhKKSYFiXRQyJwgFEoBPu75/HWEJGvcuLHaIQ0FHTiiesBI06ZN4e/vn+f90dHRamU1atTQPshcfHx81Pb209S+rvQZq7W1Nby9vQtsn9Q5OTlJul/Tfo9S29DUjuoMVyIiIiIio2kwDPBu8b9rr2Bg1Bmg+WeAnJNnihKTgkQ6sDIv3JeOq60lWtf00FM0lE11tuC+ffvw8uVLjfeePn0ad+/eFZXlN0sQAGJjY9XKHB0dJUaZRSaTqdV9+/atTm1pos9YAfXElD5jLcmkHOpiyDaIiIiIiLSRkFoEf0w2MwO6/wCUcQHaLwA+Pgy4Vzd8v6SGSUEiHfi628FMx30FzWTAoMaVYSHnl5++DRgwAPb2/zvmPjMzM88DR1RnETo5OantS6gqMTFRdC2TyWBjY6NjtICtrXi2aEJCgs5tqVKNVVN/UhgyViIiIiIiMq64lAx8tfMWOqw4XTSJQZeqwMTbQNOxgJnc8P2RRsxKEOnAx90OZSzkkhODZjKgjKUcAxqpHyZAhWdnZ4fBgweLytatWwdBEC/4jo2NxY4dO0RlgwYNQpkyZQpsPzdBEJCcnKxzvElJ4hOocyc0C0vT3nSq/UlhyFiJiIiIiMh4Dt1+iXbLT2HLpSd4EZeKbw+HFU3HltxSy9i4WJtMzqetfTC8RRVjh5EvC7kZrj15i8HrLgIQoNRik0EzGWAmk2HdkGCUdcg63XZOD39M72qam6haFnKJtLGMHj0aP/30U871o0ePcPToUbRv3z6nbOPGjUhNTRXVGzlyZIFtOzs7q5XFxcXpPFtQ9fAHXfaOy0tesepKdbmwPmMlIiIiIqKi9youFTP33MaRkNei8k0XItCjrieCKrsYKTIqKkwKksmxMpfDytz0pw838XHFpmGNMHzjZaSkK/JNDGbPEFw3JBiNq7rmlFtbyGFtYfrvtTgJCAhA8+bNcebMmZyyNWvWiJKCqgeMNGnSBAEBAQW27ebmplYWFhaG8uXLS44zPDxc7fAHTe3rKq9YmzRpIrmttLQ0PH78uMD2iYiIiIjI9CmVAv649ARLDt5FQlqm2uuCAEzdcQv7xjcvFr+bk+6K51QgIhPRxMcVxye1wrh3q8HF1hIAIDeTwdxMBvn/ry12tbXEuHer4fikVqKEIBnOqFGjRNd79+7F69dZf/06e/Ys7ty5I3q9oANGstWrV0+t7OrVqzrFqKle/fr1dWpLE33GeuPGDWRmin9Y0GesRERERERUNB5EJuD9NecxffdtjQnBbPcjE7Hq5MMijIyMgUlBokIq62CNie2q4+K0NlgzOAiT29fAqJY+mNy+BtYMDsKFaW0wsV31nCXDZHjvvfeeaCZbRkYG1q9fD0D9gBFHR0e8//77WrUbFBQES0tLUdnu3bt1ilF1T0MAOs3iy4unpycqVRLvXbl37161/RW1YehYiYiIiIjI8H45/RCdvz+Dy49jtbp/5YkHeBDJAwZLMiYFifTEQm6G9v7lMLqVDyZ3qIHRrXzQ3r8cTxk2AisrK3z88ceisrVr1yI2Nhbbtm0TlWtzwEjudps3by4qO3v2LEJCQiTF9/r1a+zdu1dU5uvri8qVK0tqpyBt27YVXT958gSHDh2S1EZKSgo2b94sKnNwcEDDhg0LHR8RERERERUda0s50hVKre9PVygxdcctKLXZRJ+KJWYriKhEGjlyJGSy/x0PHR4ejo8//hgpKSmi+7RdOpxNdWmyIAiYMGGCpDamTJmidtDJ6NGjJbWhDdVYAWDSpElqexnmZ9GiRXjx4oWobMiQIVonUomIiIiIyDQMbFgJDSqrH0iYnysRsfjj0hMDRUTGxqQgEZVIVatWRYcOHURlqkt9GzVqhDp16khqt1evXqhYsaKo7NixY5g5c6ZW9X/++Wds2rRJVGZvb682s1EfgoOD1Zb5hoaGYsSIEVotI967dy8WLVokKpPL5Rg7dqxe4yQiIiIiIsMzM5NhUe/asJDLCr45lyUH7+JVXGrBNxqTIu/9ESlvTAoSUYmlaaZcblJnCQKAubm52r6EADBv3jyMGjUKCQma99xIS0vDtGnTNCbUli9fDicnJ8mxaGPVqlVq+yBu2LABffr0yTl8RZVSqcSKFSvw/vvvqx0wMnXqVFSvXt0gsRIRERERkWFVK2uPMa19JdVJSMvErL23DRRRISkygFPfAL+0BjLTjB1NsWNu7ACIiAyla9eu8PLywrNnz9Rec3R0RP/+/XVqt2PHjhg7dix+/PFHUfnq1avx559/olevXggKCoK7uzvevHmDW7duYfv27YiMjFRrq2fPnhg+fLhOcWijTp06WLhwISZPniwq37VrFw4dOoRu3bqhWbNmKFu2LBISEnD37l1s374dERERam0FBwdj1qxZWve9atUqrFq1Ks/XnzxRX4bQuXNntSRmNk9PTxw4cECrvmfOnKm2b2NuDx48UCurW7dunvc3aNAAa9eu1apvIiIiIiJTNrqVD/bdfIkHkYla1zl85zUO3X6JjgHlDRiZRC9vAns+BV7dyro+9Q3QZoZxYypmmBQkohJLLpfjk08+0bi0d+DAgbCxsdG57e+//x5paWn45ZdfROVv377F+vXrc047zk+vXr2wZcsWnWPQ1qRJk5CUlKSW0EtJScHWrVuxdevWAtto2rQp9u3bBwsLC637ffXqFW7cuCEp1tDQ0Dxfe/v2rdbtPHnyRHLf+d1vqJmcRERERERFzcpcjsW9a+O9Vecl1Zu55w6a+LjBsYz2vxMYRGY68M9S4J9lgDLXyqYzKwC/roBnPePFVsxw+TARlWjDhw+Hubn63z90WTqcm5mZGdasWYOlS5fC3t5eUl0rKytMmzYN27Ztg5WVVaHi0NbMmTOxceNGeHh4SKqXnVg9evQonJ2lbUpMRERERESmqYG3CwY1riSpTmRCGpYcumugiLT04nrWUuFTS8QJQQAQFMDuMVlJQ9IKk4JEVKKVL18enp6eorKGDRsiMDBQL+1PmjQJDx48wOeffw5vb+8CYxk5ciTCwsKwYMECyOVyvcSgrcGDB+PBgweYPXs2/Pz88r3XxcUFAwcOxPXr17F69epCzaokIiIiIiLT80XHmijrIG2Swh8Xn+DSozcGiigfmWnA3/OAX94FXuezv2HknaxZhKQVmaDNEZRUbJ05cwYtWrTIuf7nn3/QvHlzvfaRmpqKR48eoUqVKrC2ttZr20SFdfLkSbRu3VpUtnbtWgwbNswg/YWGhiIkJASRkZGIjY2Fg4MDPDw8UL16dQQGBkImk3bSlyE9evQI169fR2RkJGJiYmBrawsPDw9UqVIFwcHBRZ60pOKJ/wYQERERFV9H7rzCJ5uuSqrj426L/eNbwNqiiH5feH41awZgVN5bDYmYmQMjTgDl6xg2LhMkNQfEPQWJqERT3fPPwcFB5wNGtOHn51fgLDxTUaVKFVSpUsXYYRARERERkZG09y+HTgHlcPD2K63rhEcl4acTD/B5+xoGjCyX+0e1TwgCWcuK93yalRiUG3n/QxPH5cNEVGJFRUVh+/btorJBgwbB1tbWSBERERERERGZljnd/WFvLW3O2M+nwnHvdYKBIlLR/HOgbIC0Oq9uZR08QvliUpCISqwVK1YgPV28yeyYMWOMFA0REREREZHp8XCwxledpK12ylAImLrjJpTKItiRztwS6PkTIJO4XPnUN8DrO4aJqYRgUpCISqQHDx7gu+++E5W1bdsWtWrVMk5AREREREREJqp/cEU0rOIiqc6/T95i88UIA0Wkonwg0OJzaXWUGcDu0YAiwzAxlQBMChJRiXPkyBF07NgRKSkpovI5c+YYKSIiIiIiIiLTZWYmw6LetWFpLi1N9M2hMLx4m1LwjfrwzhTAXeL+7S9vAGe/N0w8JQCTgkRUrL148QJ169ZF3bp14e/vD3t7e3To0AHh4eGi+3r37o2mTZsaKUoiIiIiIiLT5uNuh3GtfSXVSUzLxMw9tyEIRbGM2ErHZcRLgEgJB5WUIkwKElGxlp6ejhs3buDGjRsICQlBYmKi2j3lypXDTz/9ZIToiIiIiIiIio+RLX1Qo6y9pDrHQiNx4Jb2pxcXSoX6QLPx0uoo0oHdnwKKTMPEVIwxKUhEJZq3tzeOHj2KsmXLGjsUIiIiIiIik2ZpboZFfWpDJpNWb9beO4hLLqK9+1pOBdxqSKvz4l/g/I+GiacYk3bmdAmWnp6Ou3fv4vHjx3j+/DkSEhKQkZEBBwcHuLq6ok6dOvDz84NcLnGaagHS0tJw+fJl3L17FzExMVAoFLC3t0flypVRq1Yt+PpKm7pLVNrJ5XI4OTkhICAAvXr1wrBhw2BnZ2fssIiIiIiIiIqF+pWcMaSJN34791jrOtGJaVh0MBSL+9QxXGDZLKyzlhGvawcISu3rnVgI1OgMuFc3XGzFTKlOCm7fvh3Hjh3D2bNncffuXWRm5j+V1NHRER988AEmTJiAmjVrFqrvmzdv4ttvv8XOnTuRnJyc531ubm5o164dxo0bhyZNmhSqT6KSyNvbu2j2ryAiIiIiIiolJneogSN3XuFFXKrWdf57+Sl61K2AJj6uBozs/3k1AJqMBc79oH0dRRqw51Pg48OAmX4nfBVXpXr58GeffYbVq1fj9u3bBSYEASAuLg6rVq1CnTp1MHv2bJ0SEWlpaZg4cSLq1auHzZs355sQBIDo6Ghs2bIFe/bskdwXEREREREREZFUdlbmmNczQHK9abtuITVDYYCINGg9DXCVuLry2WXgAvebz1aqk4KaWFtbo3r16ggODkZQUBAqV64Mmcpi+oyMDMyZMwfDhw+X1HZ8fDzatWuH7777DkqleIqrq6sr/P390bBhQ9SoUQNWVlaFfi9ERERERERERLpo41cWXeqUl1TnUXQS/nP8voEiUmFRBujxEwCJGyAenw9EPzBISMVNqU8Kenp6YsSIEdi0aRMePHiApKQkhIWF4dKlS7hy5QoeP36MmJgYrFmzBl5eXqK6v/76K9avX69VPxkZGejVqxf++eefnDIbGxt8/fXXuH37NqKjo3H79m1cvHgRd+/eRWJiIq5fv47FixejTp0iWJNPRERERERERJTL7G7+cCxjIanO6lMPEfoy3kARqajUCGj8qbQ6manAnjGAsohmNJqwUp0UPHDgAJ49e4Y1a9Zg0KBB8PHxgZmZ+iNxdnbGiBEjcPPmTdSvX1/02tdff60260+TJUuW4Pjx4znX/v7+CAkJwfz58+Hv7692v7m5OQIDA/Hll1/ixo0b+PLLL3V4h0REREREREREunG3t8LXnf0k1clUCpi68xYUyiLa+/3d6YBLVWl1nl4ALq0xTDzFSKlOCtapU0dtaXB+nJ2dsXnzZlGdly9f4uzZs/nWCwsLw/z583Ouvb29ceLECVSuXFlS30RERERERERERalvAy80qSrt8JAbT99ig4TTiwvF0gbosRKSlxEfmwPEhBskpOKiVCcFdeHn54egoCBRWWhoaL51pk6dirS0tJzrlStXwt3d3SDxERERERERERHpi0wmw8LetWFpLi2FtPRIGJ7F5n+4qt5Ubgo0GimtTmYKsHccoMXqz5KKSUEd+Pj4iK6jo6PzvPfly5fYt29fznWDBg3QuXNng8VGRERERERERKRPVdxsMaFNNUl1ktMVmLH7NgShiJYRt5kJOHtLqxNxFri81iDhFAdMCuogNTVVdO3k5JTnvRs2bEBmZmbO9aBBgwwVFhERERERERGRQXzyTlXULGcvqc6JsCj8dfOlgSJSYWkLdP9Rer1js4E3j/QeTnHApKBEgiDg8uXLojLV5cS57d+/X3TdunVrg8RFRERERERERGQoFnIzLOlTB2YSt+6bs/cOYpPSDROUqiotgODh0upkJAEbugGnlwGh+wBFhmFiM0FMCkr066+/4sWLFznXNWvWRMOGDTXeq1Ao8O+//+ZcW1paws8v69Se9PR0bNu2Dd27d4evry/KlCkDFxcX+Pn5YciQIfjzzz9FMwyJiIiIiIiIiIwpsKIThjatIqlOfGoGLj9+Y6CINGg7B3CsJK1O3FPgxHzgz4HAsprAiYVAfBHNcDQiJgUl2LBhAz799NOcazMzM/z44495nmAcEhKC5OT/barp5eUFCwsL/PvvvwgMDES/fv3w119/ITw8HKmpqYiNjcXdu3exceNG9O/fH/7+/jh06JDB3xcRERERERERkTYmta+OCk5ltLo3qLIzDoxvgfb+5QwcVS5WdkCP/0ivJ/z/gSPJ0cDppcCPQcCjf/Qbm4kxN3YApuTevXt48uRJznVGRgZiY2Nx+/Zt7NmzByEhITmvWVpaYs2aNWjTpk2e7T148EB07eDggJMnT6JDhw5ITy946uy9e/fQpUsX/PDDDxgzZowO74iIiIiIiIiISH9srcwxv1cAPlp/Oc977KzM8WWnmhjYsBLMpK431oeqrYCgocDV33SrLyiAjBRgU09g8O6sZcklEJOCufz000/4/vvv871HJpOhY8eOWLRoEQIDA/O99+3bt2rXffr0yUkIurq6YsCAAWjSpAkcHR3x6tUrHDlyBDt27MhZOqxUKjF27FhUrFgR3bt31+p9pKWlIS0tDQCQlJSkVR0iIiIiIiIiIm20ruGBHnU9sef6C7XX2tUqi7k9/FHeUbvZhAbTbh5w/xgQ/0y3+tkzB7f0B8ZeARzK6y82E8GkoER9+/bF+PHjC0wIAupJwcePH+f8f6dOnbBp0ya4urqK7vn4449x48YNdOvWDU+fPhWV379/H87OzgX2u2jRIsyZM6fA+4iIiIiIiIiIdDGjay2cuheFt8lZB3O421thbnd/dAwol+c2a0XK2gHo/j2wuY/ubQhKICM5a8Zh66/0Fpqp4J6CEm3duhXNmzfHO++8o7Y8WFViYqLG8vr162PXrl1qCcFsgYGBOHbsGGxsbHLKYmJi8PPPP2sV41dffYW4uDjExcVxT0IiIiIiIiIi0js3OytM71ILAPBBw0o49nlLdKpd3jQSgtl82wJ1BxauDUEJXFlXIk8lZlIwl++++w6CIOR8JCcn4+nTp9i3bx+GDRuGMmX+N/X1n3/+QXBwMK5cuZJne9bW1hrLV65cCSsrq3xjqV69Or744gtR2Zo1a7R6H1ZWVnBwcICDgwNsbW21qkNEREREREREJEWf+hWwb1xzLOpdG45lLIwdjmZVWxW+jaQo4P6RwrdjYpgUzEeZMmXg5eWFLl26YO3atbh58ybq1q2b8/rbt2/Rs2dPtWXC2ezs7NTKAgIC0LhxY636HzFihCjDHhERgYiICEnvgYiIiIiIiIjIEGQyGQIqOBo7jPzFPQNkhUx/yeRA9D39xGNCmBSUwNfXF0ePHkXFihVzyp4/f45vv/1W4/2akoItW7bUuj9PT0/4+vqKyvKbmUhERERERERERLmkJ2Ul9QpDZgakad4irjhjUlAiNzc3tUM8fvvtN433li1bVq2sevXqkvqrUaOG6DoyMlJSfSIiIiIiIiKiUsvSFoCycG0ISsBKfeJXccekoA569eolWtb74sULjct6/fz81MocHBwk9aV6f2xsrKT6RERERERERESlllt1QKkoXBuCIqudEoZJQR04OTnBxcVFVPbq1Su1+ypWrAh7e3tRWVpamqS+UlNTRde5TyQmIiIiIiIiIqJ8VO8A2LgVrg1bd6Bae/3EY0KYFNQTCwvNp+zUq1dPdP369WtJ7aouF3Z1dZUWGBERERERERFRaSW3AIKH6b6voMwMaDAsq50ShklBHSQkJODNmzeiMk37BwJA9+7dRddXr17Vuh+FQoHr16+LylT3GCQiIiIiIiIionwEfQRYWEs/hVhmBljYAEFDDRKWsTEpqIP9+/dDEISca3d3d5QvX17jvb169RJdHzt2DPHx8Vr1c+jQISQm/u90G3t7ewQFBekQMRGVBDKZTPSR1yFHRERERERElItDeeCDP7OSfNomBrPvHfBnVv0SyNzYARQ3KSkpmDVrlqisa9euMDPTPKiqVq2Ktm3b4tixYwCA5ORkLFu2TO0EY1VKpRLz588XlfXu3RtyeSGP0SYiKmUyMjJw69YthIaGIjY2FnFxcbC2toaTkxMqVqyIBg0aqO0TS0RERERERevuq6wJVDXLSTugVWtVWgCDdwNb+gMZKVmHh+Qle4bggD8B7+aGiccElNqk4BdffIG+ffsiODhY6zpv3rzB+++/j3v37uWUyeVyTJw4Md96ixYtykkKZl83adIEHTt2zLPO1KlTceHChZxrmUyGL7/8UutYiYhKM0EQcPjwYaxevRqHDh1SO7RJVUBAAIYNG4ahQ4fCycmpaIIkIiIiIiKkZijwn+P3sfrUQ1Qva489Y5vBQm6gha1VWgBjrwBXfwMurwWSo7P2GpSZAYIyK1Fo6561h2DQ0BI7QzBbqV0+fOTIETRs2BCNGjXC8uXLcf36dWRkZKjdJwgC7t69i3nz5qFGjRqi5B4ATJw4EbVr1863rwYNGmDIkCE51xkZGejRowdmz56NqKgo0b13795F37598e2334rKp06dCj8/P6lvk4io1Hn06BHatm2LTp06Yffu3QUmBAHg9u3bmDhxIqpXr45t27YVQZRERERERHThYQw6ff8PVp4IR6ZSQMjLeKw788iwnTqUB1p/BUy6C/T/A2gzA2g2Ieu//f8APg/Ner2EJwSBUjxTMNulS5dw6dIlAIClpSUqVKgAJycnWFpaIiEhAU+fPkVCQoLGukOGDMGSJUu06mflypW4c+cOrly5AgBIT0/HnDlzMH/+fPj4+MDR0RGvXr3C06dP1ep26tQJ8+bN0/EdEhGVHjdu3MC7776rdhiUtqKiotCvXz/Mnz8fX3/9tZ6jIyIiIiIiAIhLzsCig6H472X1HMiKo/fQKaAcKrvaGjYIuQVQswuALobtx4SV+qRgbunp6Xj0qOCMtIODAxYvXoxRo0ZBJpNp1batrS2OHj2KDz74AIcOHcopVygUouXIqj755BOsXLmSewkSERUgMjIS7dq105gQrFq1Krp27YqAgAA4OTkhJSUFjx8/xvHjx3Hq1Cm1+6dPnw5PT0989NFHRRE6EREREVGpIAgCDt5+hZl77iA6MU3jPWmZSkzbdQubhzXSOudCuim1ScEtW7bgr7/+wtGjR3Hp0qUCTwSWyWSoXbs2Bg8ejCFDhsDd3V1yn05OTjhw4AC2bNmCJUuW4ObNmxrvMzc3R6tWrTB79mw0a9ZMcj9ERKXRl19+qbYlg42NDb777jsMGzZM44FQM2fOxL///ovBgwcjJCRE9NqUKVPQvXt3uLq6GjRuIiIiIqLS4GVcCmbsvoNjoa8LvPfsgxjs+Pc53gvyKoLISq9SmxT08/ODn58fvvjiCyiVSty/fx8PHjzAkydPEB8fj4yMDNjb28PR0RHe3t6oX78+HBwKfwKOTCbDgAEDMGDAAISHh+PSpUt49uwZ0tPT4erqCi8vL7Ro0QKOjo56eJdERKXDmzdvsHnzZlGZTCbDtm3b0Llz53zr1q9fH6dPn0bjxo3x4MGDnPKYmBj8/vvvGD9+vEFiJiIiIiIqLeJTM9Dxu38Ql6J+lkNe5u8PQasa7nCzszJgZKVbqU0K5mZmZoYaNWqgRo0aRdqvj48PfHx8irRPIqKS6MCBA8jMzBSV9e7du8CEYDZXV1csXboUPXv2FJXv3buXSUEiIiIiokJysLbABw0rYdWpcK3rvE3OwNy/QvDDB/UMGFnpVmpPHyYiopIjLCxMrax///6S2ujSpYvajPD89nwlIiIiIiLtfda2Giq72kiqs/fGC5wIizRQRMSZgkREenT37l2EhIQgMjISb968gZOTEzw8PFCtWjUEBgYaOzyRx48f48aNG4iMjER0dDTs7Ozg4eGBKlWqICgoqFgdcBQZqf6DgtTZ3+bm5vDx8cG1a9fybVdXERERuHz5MiIiIpCamgpHR0f4+/ujSZMmsLa21qqNuLg4XLx4Effu3UN8fDwcHBzg5eWFVq1awcnJSW+xEhERERHpm7WFHAt71cbAtRcl1Zu+6zaOTHwHtlZMYekbnyiRvigygHuHgeh7QHoSYGkLuFUHqnfIOuqc9Gr37t3o1auXqGzPnj3o3r27zm0uWbIEU6dOFZWFhITAz88v33qRkZH45ptvsHPnznxPMPf09ET37t0xdepUVK5cWec4CyMhIQHLly/H1q1b1Q7WyM3FxQWdO3fG1KlT4e/vr1Xbvr6+CA//33KAFi1a4PTp0zrHmpKSgnLlyokOgho4cKDa3oEAYGlpqVVZQVTraJOsmz17NubMmZNzXblyZTx+/DjneufOnVi0aBGuXLmisb6zszPGjBmDadOmoUyZMhrvuXPnDubMmYM9e/YgPT1d7XULCwv07NkTy5YtQ8WKFQuMmYiIiIjIGJr5uqFvkBe2XX2mdZ3nb1Ow7Mg9zOxWy4CRlU5cPkxUWPEvgRMLgWU1gT8HAifmA2e/z/rvnwOzyk8szLqP9KZbt27w8hKfRLVmzRqd2xMEAWvXrhWVtWjRosCE4PLly1GtWjUsW7Ys34QgALx48QKrVq1CzZo1MX36dCgUCp3j1cXmzZtRrVo1zJ49O9+EIPC/gzsCAwMxatQopKSkFNj+hx9+KLo+c+ZMgc8kP7t371Y7GX7IkCEa7/X29lYre/ZM+x808qpTpUoVyW1kS0lJQb9+/dCnT588E4IAEBsbi/nz56Nx48Z4+VL9+8SyZctQt25dbNu2TWNCEAAyMjKwbds21KpVC//884/OMRMRERERGdrXXfzgZiftD/jrzz3C9advDRNQKcakIFFhPPoH+DEIOL0USI7OKlMqAGVG1n+BrPLTS7Pue8Rf1vVFLpdjxIgRorJDhw7h6dOnOrV3/Phx0cmzAPDJJ5/keb9SqcTIkSMxadIktcRVQVJTU7FgwQL07dsXaWlpOsUr1fz58zF48GC8fv1aUj2FQoHVq1ejXbt2iI2NzffewYMHQyaT5VwLgoBNmzbpFC8AbNy4UXRdoUIFtGnTRuO9rVu3Vis7dOiQpP5u3bqF58+fi8reffddSW1kS09PR9euXbFt2zat69y8eRNdunQRJWC/+uorTJ48We0QlbwkJiaiS5cuCA0NlRwzEREREVFRcLKxxMxu2q1GyiYIwNQdN5GhUBooqtKJy4fJ9GSmZX2YMrkF8OwKsKknICizPvIjKICMlKz7B+8GqrTIKs9IyVp2bIrMrbI+TNjw4cMxb968nISJQqHAunXrMHv2bMltqc4ydHFxwXvvvZfn/ePHj9c4M9HR0RE9e/ZEUFAQPDw88ObNG9y6dQvbt29HVFSU6N5du3ahf//+2LVrl+R4pVi6dClmzJihVl6mTBl06dIFzZo1Q/ny5REfH4+7d+9i+/btePLkiejes2fPokOHDjh79iwsLDQvh69SpYrakuFNmzZh5syZkmN+9eoVjh49KiobNGgQzMw0/y2rfv36aNCggWhG3urVqzFhwgS1GaWaCIKAadOmicrkcjlGjhwpOXYAmDRpEo4fP55z3aBBA3Tu3BlVqlSBtbU1nj17hgMHDuDEiROieteuXcPChQsxb948bNy4EYsXL855rXLlyujevTv8/f3h7OyMN2/e4PTp09ixY4doBmFCQgJGjx6NkydP6hQ7EREREZGhdatTHrv+fYYTYVEF3/z/7r5KwJrTDzGmta8BIytdZIIgCMYOggznzJkzaNGiRc71P//8g+bNm+u1j9TUVDx69Cjnl91CO7EIOLW44PuMKaAPcO9QVlKvoIRgbjIzwMIGGHsFcCgP7BkLXNN9JpVBtZwKtP7K2FEUqE+fPti5c2fOdcWKFfHo0SNJh2RERUXBy8tLlFiZMGECvvvuO433HzhwAF26dFErHzFiBJYuXap2gi0ApKWlYebMmfj222+h+m13zZo1arMeNck9Cw8A1q9fj6FDh+Zb58aNG2jYsKHastMePXpg1apVKFeunFodpVKJ5cuXY/r06WozGadNm4YFCxbk2d+6deswfPhwUdnZs2fRtGnTfONUtWzZMkyePFlUdufOHdSqlfc+IhcvXkSzZs1Ey7L9/f3x119/5bsMOD09HRMmTMCqVatE5VOnTsWiRYsKjFV1T0FLS0tkZGRAEARUrFgRa9euRfv27TXW3blzJz744APR58fW1hYXL15E48aNkZiYCCsrKyxbtgyjRo3SOK5DQkLQsWNHtVmyx48f1ziDUt/0/m8AEREREZUKz9+moN3yU0hO135bJUtzMxz+7B1UcbM1YGTFl9QcEJcPE+ki+j6QkSotIQhk3Z+RDFz9zSBhlUajR48WXT99+hQHDx6U1MZvv/2mljTLa+lwZmamxtlj06dPx5o1azQmBAHAysoKS5Yswffff6/22ueff17g0lxdjRo1Su29ffjhh9i1a5fGhCAAmJmZYfLkyfjvf/+rloRasmQJwsLC8uyvb9++aodlqC4D1oZqnQYNGuSbEASARo0aYd26daLZhHfu3EGdOnUwceJEnDx5EjExMcjMzERCQgJu3bqF77//HrVr11ZLCPbv3x/z58+XHDeQlWQUBAHe3t44e/ZsnglBAOjduze+/fZbUVlSUhJat26NxMREWFpa4tChQxgzZkyeie5atWph165darMoN2zYoFP8RERERERFoYJTGUzpUENSnfRMJb7aeVNtogXphklBIl1Eh2UtCdaFoASurDPdZcPFTJs2bVCtWjVRmdQDR3755RfRdbNmzfJMQO3cuVPtMIq2bdti3rx5WvU1btw4DBgwQFSWmJiIX3/9VULE2rl06RIuXLggKvPz88PatWvVZh1q0rNnT3z55ZeiMoVCgR9//DHPOg4ODujZs6eobOvWrZL2Trxx4wZu3rwpKlM9xCQvQ4YMwdGjR0UHjyQmJuK7775D69at4ebmBgsLCzg4OKBOnTr47LPPcO/ePVH8y5cvxx9//CFptqkqmUyGTZs2aXUS8Keffgp3d3dRWfZS87lz56JVq1YFthEUFISuXbuKyg4fPqx9wERERERERvBhE2/Uregkqc6Fh2+w9Ypue8mTGJOCRLoo7J6HSVHA/SP6iaWUk8lkGDVqlKjswIEDagdG5OXkyZO4f/++qCy/feRUZ5QB0Dj7Lz9Lly6FlZV4v8affvpJUhva0BTrsmXL8twTUJOvv/5abUbhhg0bkJycnGcd1ROCY2Nj8ddff2ndp+osQQsLC3zwwQda13/33Xdx7949bNy4UevtEtzc3LB8+XI8fvwYEydO1Cppmp/OnTtr3be5ublaQi87ps8++0zrPnv37i26fvXqFSIjI7WuT0RERERU1ORmMizuUxvmZtJ+/l6wPxSRCakGiqr0YFKQSCeFSxhAJgei7xV8H2ll6NChor3MFAqF1jPvVGcVOjs7o2/fvhrvTU1NxZkzZ0Rl+c0qzEv58uXRrVs3UdnDhw/x+PFjSe0U5NixY6LrihUromPHjpLasLGxwaBBg0RlCQkJuHTpUp512rZti/Lly4vKtF1CrFAo8Mcff4jKOnfuDDc3Ny0jzjo05NChQ9i4caPaTMm8REdHY8GCBZg/fz5evnypdV95KWivR1WBgYFqZf3791dLHkttI7+l3kREREREpqBmOQeMbFlVUp341EzM+SvEQBGVHkwKEumksElBMyAtUT+hEFxcXNCvXz9R2bp166BU5r/nY0xMjOiQEgAYPHhwnoclXL16FRkZ4mXfvXr10iFiaDzZ+Pz58zq1pcmLFy/UDp7o0aOHTjPgpMYql8vVEomHDh1SO31ZkyNHjuDVq1eiMtWZh/l59uwZ2rRpg+7du+PYsWM5J1MDWbNKy5cvj1q1aqFy5cpqn+eYmBgsX74cNWvWxH//+1+t+9RE6oFOlSpVUitr1qyZpDYqV66sVhYXFyepDSIiIiIiYxj3bjVUlXh4yP6bL3Es5LWBIiodmBQk0kkhNzUVlICVnX5CIQDqB45EREQUuKfahg0b1Pa6y+uAEQC4fv26WllQUJD2QRZQ79q1azq1pYmmtnSNNTAwEObm5gW2n5vqHoAZGRnYsmVLgX2pzih0dXXVeNKzJg8ePEDjxo1x4sQJUXmdOnWwefNmREVF4cWLF7hz5w4eP36M+Ph4nD17FoMHDxYd0hEfH48PPvhA4/JrbdjY2OR5iEte7OzUvx/4+PgUug0mBYmIiIioOLC2kGNh79qS683YcxsJqdyvX1dMChLppLBJQQXgVl0/oRAAoHHjxqhbt66orKADR1QPGGnatCn8/f3zvD86OlqtrEYNaadlZfPx8VHb209T+7rSZ6zW1taigzvyaj+3gIAA1K9fX1RW0BLi+Ph47NmzR1TWv39/WFpaFhhjSkoKunXrpraX5GeffYarV69i4MCBcHV1Fb1mYWGBpk2bYuPGjThy5AgcHR1Fr48dOxYXL14ssG9VTk5Okuto2udRajua2lCd2UpEREREZKoaV3VF/+CCD+rL7WVcKpYe5pY5umJSkEgX5trv86WRrTtQrb1+YqEcqrMF9+3bl+f+cKdPn8bdu3dFZfnNEgSyDsxQpZpI0pZMJlOr+/btW53a0kSfsQLqCSptYlWdLXj16lWEhOS978e2bduQkpKSbxt5WbJkidrnc+DAgVixYoXaLEdN2rRpg61bt4rKFAoFxo4dq1X/uUk5yKUo2iEiIiIiKi6+6uQHNztpv29vvBCBqxHqv/9QwZgUJNKFW42sw0J0ITMDGgwD5PyFX98GDBgAe3v7nOvMzMw8DxxRnUXo5OSkti+hqsRE8T6QMpkMNjY2OkYL2NqK98xISEjQuS1VqrFq6k8KXWIdMGCAWmJr06ZNed6v+lrNmjXRsGHDAvvJyMhQO73ZxsYGy5YtK7Bubu3bt1fbI/LKlSs6zRYkIiIiIiLpHG0sMLdH3qu3NBEE4KudN5Gemf+e8qSOSUEiXbhVAyyssxJ8UsjMAAsbIGioQcIq7ezs7DB48GBR2bp16yAI4uXesbGx2LFjh6hs0KBBKFOmTIHt5yYIApKTk3WONykpSXSdO6FZWJr2l1PtTwpdYnV3d1c77fj333/XeABMREQETp8+LSrTdpbglStX1A4xadeuHcqWLatV/dxUD0gBgKNHj0puh4iIiIiIdNMpoBza+kn7Wf7e60SsPhVuoIhKroLXVBEVtRafA03GGDuK/MktgGdXgE09s64FLf4iITPL+hjwJ+BQPqus87dAh4UGC7NQCrtE2khGjx4tmjX26NEjHD16FO3b/2+59saNG5GamiqqN3LkyALbdnZ2ViuLi4vTebag6iEQuuxFl5e8YtWV6nJhbWMdMmQI/vrrr5zrp0+f4sSJE2jTpo3ovk2bNomSt2ZmZmoJ3rzcvHlTrUybGYaaNGrUSK3szp07OrVFRERERETSyWQyzOvpjwsPY5CYlql1vf8cf4BOtcvD14OHemqLSUEyPeZWxSMhVaUFMHg3sKU/kJGSdXhIXrJnCA74E/Bu/r9yizJZH6Q3AQEBaN68Oc6cOZNTtmbNGlFSUPWAkSZNmiAgIKDAtt3c3NTKwsLCUL58eclxhoeHqx0Coal9XeUVa5MmTSS3lZaWhsePHxfYvibdunWDs7OzaI/DjRs3akwK5ta6dWt4eXlp1UdMTIxama7P0t3dXa3szZs3OrVFRERERES6Ke9YBl90rIGZe7T/A326QolpO2/hv580hpmZzIDRlRxcPkxUGFVaAGOvAO9MAWz+PwkhkwNmFv/bc9DWHXjni6z7cicEyWBGjRolut67dy9ev34NADh79qzazK+CDhjJVq9ePbWyq1ev6hSjpnqqp/UWhj5jvXHjBjIzxX+h0zZWS0tL9O/fX1S2c+dO0XLkCxcu4N69e6J7hgwZonV81tbWamWqB5ZoS9Ny8MLsG0lERERERLoZ1Kgy6ldyklTn0uM3+O/lp4YJqARiUpCosBzKA62/AibdBfr/AbSZATSbkPXf/n8An4dmve4gfTYZ6ea9994TzRTLyMjA+vXrAagfMOLo6Ij3339fq3aDgoJgaWkpKtu9e7dOMaruaQhAp1l8efH09ESlSpVEZXv37lXbX1EbhY1VdW/AxMRE7Ny5M+d648aNotft7OzQu3dvrdvXNLtPdWajth49eqRWps8ZnEREREREpB0zMxkW96kDC7m0WX+LDobidXxqwTcSk4JEeiO3AGp2AZpPzEoINp+Ydc1ThouclZUVPv74Y1HZ2rVrERsbi23btonKtTlgJHe7zZuLZ3uePXsWISEhkuJ7/fo19u7dKyrz9fVF5cqVJbVTkLZt24qunzx5gkOHDklqIyUlBZs3bxaVOTg4SNqzr3HjxqhevbqoLDsRmJ6ejj///FP0Wp8+fSSdlOzr66tWduTIEa3r56bp+VSrVk2ntoiIiIiIqHCql7XH6FbqP+/nJyE1E7MkLDsuzZgUJKISaeTIkZDJ/vcXpfDwcHz88cdqy0q1XTqcTXVpsiAImDBhgqQ2pkyZonbQyejRoyW1oQ3VWAFg0qRJansZ5mfRokV48eKFqGzIkCFaJ1Kzqc4WPH78OJ4/f459+/ap7dmn7anD2YKDg+Ho6CgqCwkJER1woo2kpCT88MMPauXt2rWT1A4REREREenPmNY+8HHXftIAABy68wqH77wyUEQlB5OCRFQiVa1aFR06dBCVqS71bdSoEerUqSOp3V69eqFixYqismPHjmHmzJla1f/555/VDtWwt7dXm9moD8HBwWrLfENDQzFixAitlhHv3bsXixYtEpXJ5XKMHTtWciyDBw8WJWmVSiU2b96stnS4UqVKaN26taS2zc3N0bNnT7XyESNGaFwOrIlCocDgwYPx6pX4BwdfX1/UrVtXUjxERERERKQ/VuZyLO4j7fc2AJi55zbiU7WfEFEaMSlIRCWWpplyuUmdJQhkJaBU9yUEgHnz5mHUqFFISEjQWC8tLQ3Tpk3TmFBbvnw5nJycJMeijVWrVqntg7hhwwb06dMn5/AVVUqlEitWrMD777+vdsDI1KlT1ZYCa6NSpUpo1aqVqGzNmjU4cOCAqGzQoEGi5KG2Zs6cCQsL8VL9169fo1GjRti5c2e+SdB79+6hTZs22LVrl9pr8+fP1ykeIiIiIiLSn2BvFwxsVKngG3N5HZ+Gbw7dNVBEJYO5sQMgIjKUrl27wsvLC8+ePVN7zdHRUe1UXG117NgRY8eOxY8//igqX716Nf7880/06tULQUFBcHd3x5s3b3Dr1i1s374dkZGRam317NkTw4cP1ykObdSpUwcLFy7E5MmTReW7du3CoUOH0K1bNzRr1gxly5ZFQkIC7t69i+3btyMiIkKtreDgYMyaNUvnWIYMGYITJ07kXD98+FDjPbqoWrUqFixYgC+++EJUHhUVhT59+qBGjRro2LEj/P394ezsjOTkZDx58gSnTp3C8ePHoVQq1drs1asX+vXrp1M8RERERESkX192qoljoa/xOj5N6zqbLzxBz7oV0MDbxYCRFV9MChJRiSWXy/HJJ59oXNo7cOBA2NjY6Nz2999/j7S0NPzyyy+i8rdv32L9+vU5px3np1evXtiyZYvOMWhr0qRJSEpKUkvopaSkYOvWrdi6dWuBbTRt2hT79u1Tm40nRZ8+fTBmzBgkJSVpfL1Ro0Y6zULMNmXKFLx69QrLly9Xey0sLAxhYWFat9WqVSv88ccfnCVIRERERGQiHKwtMKd7AEZtviqp3pc7buLAhBawMpcbKLLii8uHiahEGz58OMzN1f/+ocvS4dzMzMywZs0aLF26FPb29pLqWllZYdq0adi2bRusrKwKFYe2Zs6ciY0bN8LDw0NSvezE6tGjR+Hs7FyoGOzs7NC7d+88X9d1lmBuy5Ytw9atW+HiottfAs3NzTF79mwcO3YM1tbWhY6HiIiIiIj0p2NAOXTwL6v1/TIZ0MzXDQplwXuql0ZMChJRiVa+fHl4enqKyho2bIjAwEC9tD9p0iQ8ePAAn3/+Oby9vQuMZeTIkQgLC8OCBQsglxftX6oGDx6MBw8eYPbs2fDz88v3XhcXFwwcOBDXr1/H6tWrCzWrMre8En+WlpY6L+dW1bdvXzx+/BgrV65EUFCQVs+5atWqmDFjBh4/foxZs2YV+eeGiIiIiIi0M7dHAOytCl74Wr2sHbaPaoq5PQJgY8mFsprIBG2OoKRi68yZM2jRokXO9T///IPmzZvrtY/U1FQ8evQIVapU4cwaMjknT55UO8127dq1GDZsmEH6Cw0NRUhICCIjIxEbGwsHBwd4eHigevXqCAwMNKnlqI8ePcL169cRGRmJmJgY2NrawsPDA1WqVEFwcHCJSYwlJibi6tWrePz4Md6+fYuEhATY2NjAyckJ5cqVQ4MGDSTPoKT/4b8BRERERFTUfr8Yga933db4mqXcDGPf9cWolj6wNC9dc+Gk5oCYKiWiEk11zz8HBwe9zUjTxM/Pr8BZeKaiSpUqqFKlirHDMDg7Ozu0bNkSLVu2NHYoRERERESkBx8EV8Keay9w6fEbUXlDbxcs7F0bvh52RoqseCldKVMiKlWioqKwfft2UdmgQYNga2trpIiIiIiIiIiosMzMZFjYuzYs5VlpLXsrcyzoFYD/ftKYCUEJOFOQiEqsFStWID09XVQ2ZswYI0VDRERERERE+uLrYYcxrX0R+jIec3r4o6wDt7KRiklBIiqRHjx4gO+++05U1rZtW9SqVcs4AREREREREZFejXvXF2ZmprNve3HD5cNEVOIcOXIEHTt2REpKiqh8zpw5RoqIiIiIiIiI9I0JwcLhTEEiKtZevHiBzp07AwAyMjLw5MkTJCYmqt3Xu3dvNG3atKjDIyIiIiIiIjJJTAoSUbGWnp6OGzdu5HtPuXLl8NNPPxVRRERERERERESmj8uHiahE8/b2xtGjR1G2bFljh0JERERERERkMjhTkIhKFLlcDicnJwQEBKBXr14YNmwY7Ox4JD0RERERERFRbkwKElGx5u3tDUEQjB0GERERERERUbHCpCAREREREREREZUqGQoljt+NRHhUIpLTFLCxksPH3Q7v1vSAhbx07LbHpCAREREREREREZUKr+NT8fvFJ9h8IQJvktIhN5NBBkAAoFAKcLG1xKDGlTGwUSWUdbA2drgGxaQgERERERERERGVeOfDYzB8w2WkZCig/P9dqBRK8XZUb5LS8ePx+1j3z0OsHRKMJj6uRoi0aJSO+ZBERERERERERFRqnQ+PweB1F0UJwbwoBSAlQ4HB6y7ifHhM0QRoBEwKEhERERERERFRifU6PhXDN1yGUhAKTAhmUwqAUhAwfONlvI5PNWyARsKkIBERERERERERlVi/X3yi1QxBVUoBSElX4I+LTwwTmJExKUhERERERERERCVShkKJzRciJCcEsykFYPOFCGQolPoNzAQwKUhERERERERERCXS8buReJOUXqg2YpLSceJupJ4iMh1MCpLeCIKOaXciIiq2+L2fiIiIiExZeFQizGSFa0NuJkN4VJJ+AjIhTApSoZmZZQ0jpbLkTaUlIqL8ZX/vz/63gIiIiIjIlCSnKWAmK1xWUAYgKS1TPwGZEP4ET4Vmbm4OAMjIyDByJEREVNQyM7N+OJLL5UaOhIiIiIhInY2VHIVd2yIAsLUy10c4JoVJQSo0MzMz2NjYID4+3tihEBFREUtISIC1tTWTgkRERERkknzc7aDQ9ZSR/6dQCvBxt9VTRKaDSUHSC0dHRyQlJXG2IBFRKaJUKpGYmAgHBwdjh0JEREREpNG7NT3gYmtZqDZcbS3RuqaHniIyHUwKkl7Y29tDJpMhNjbW2KEQEVERiY+PhyAIsLe3N3YoREREREQaWcjNMKhxZZ0PGzGTAYMaV4aFvOSl0EreOyKjkMvlcHV1RUxMDCIjI3kaJRFRCZeYmIhXr17BwcEBlpaF+8srEREREZEhDWxUCWUs5JITg2YyoIylHAMaVTJMYEbGpCDpjbu7Ozw8PBATE4OXL18iLS2NyUEiohJGqVTi7du3ePbsGezs7ODp6WnskIiIiIiI8lXWwRprhwTDTCbTOjFoJgPMZDKsGxKMsg7Whg3QSEre0SlkVK6urjA3N8fLly8RFxcHCwsL2NnZwcbGBnK5HGZmZpAV8ihwIiIqOoIgQKlUIjMzEwkJCUhMTIQgCHBwcICnpye/pxMRERFRsdDExxWbhjXC8I2XkZKuQH5nj2TPEFw3JBiNq7oWXZBFjElB0jtHR0fY29sjOTkZiYmJSEhI4F6DREQlgLW1Ndzd3WFvb88lw0RERERU7DTxccXxSa3wx8Un2HQhAm+S0iE3k0EGQEDWKcOutpYY1LgyBjSqVGJnCGZjUpAMwszMDHZ2drCzs0PZsmWhVCqhUCigVCqNHRoREUlkZmYGuVwOuVxu7FCIiIiIiAqlrIM1JrarjrHv+uLE3UiERyUhKS0Ttlbm8HG3ReuaHiXyUBFNmBQkg5PJZPxlkoiIiIiIiIhMhoXcDO39yxk7DKMqHalPIiIiIiIiIiIiysGkIBERERERERERUSnDpCAREREREREREVEpw6QgERERERERERFRKcOkIBERERERERERUSnDpCAREREREREREVEpw6QgERERERERERFRKcOkIBERERERERERUSnDpCAREREREREREVEpw6QgERERERERERFRKcOkIBERERERERERUSnDpCAREREREREREVEpw6QgERERERERERFRKcOkIBERERERERERUSnDpCAREREREREREVEpw6QgERERERERERFRKcOkIBERERERERERUSnDpCAREREREREREVEpw6QgERERERERERFRKcOkIBERERERERERUSljbuwAyLASExNF1zdv3jRSJEREREREREREZCiqOR/VnJAqJgVLuIcPH4qux4wZY6RIiIiIiIiIiIioqKjmhFRx+TAREREREREREVEpw6QgERERERERERFRKcPlwyVc165dRddVq1aFnZ2dkaLRj6SkJHTs2BGHDh2Cra2tscMh0hrHLhVHHLdUXHHsUnHFsUvFFccuFVclaewmJiaKlgyr5oRUyQRBEAwdFJE+xcfHw9HREXFxcXBwcDB2OERa49il4ojjloorjl0qrjh2qbji2KXiqjSPXS4fJiIiIiIiIiIiKmWYFKRix8rKCrNmzYKVlZWxQyGShGOXiiOOWyquOHapuOLYpeKKY5eKq9I8drl8mIiIiIiIiIiIqJThTEEiIiIiIiIiIqJShklBIiIiIiIiIiKiUoZJQSIiIiIiIiIiolKGSUEiIiIiIiIiIqJSxtzYAVDJFh4ejkuXLuHZs2dIT0+Hs7MzatasiaZNm8La2trY4RFpZGrjNiMjA2FhYbhz5w5ev36NhIQE2NnZwdXVFXXq1EFAQADMzPg3HjK9sRsfH4+7d+8iIiICL1++RFJSEgDAyckJ5cqVQ/369VG5cuUij4tMj6mNXSJtcexScWTq41ahUODq1asICQlBZGQkMjIyYGdnBy8vL/j5+aFmzZr82beUMvWxWywJRAawa9cuoX79+gIAjR92dnbC2LFjhaioqCKLSalUCiEhIcJvv/0mfPrpp0JQUJBgYWEhimvIkCFFFg+ZHlMatw8fPhS++eYboV27dkKZMmXyjAmA4OjoKIwZM0a4d++eweMi02QqYzcpKUlYuXKl8P777wve3t75jtvsD29vb2HOnDlCTEyMQWMj02QqY1dbSUlJgo+Pj1qc/Pmh9DGlsduyZUutvt/m9bF+/XqDx0imwZTGrSYPHz4URo8eLTg5OeU7Zh0cHIQePXoI+/fvN0qcVPRMZexWrly5UN9vTfFnByYFSa9SU1OFgQMHav2F4O7uLpw6dcqgMf36669CmzZtBEdHx2LzhUlFy5TGbWpqqtCoUSOd/mGxtLQUvv32W0GpVBokNjI9pjR2BUEQ7t+/r/MPRh4eHsKOHTsMFhuZFlMbu9qaOHEif34o5Uxx7DIpSAUxxXGbm0KhEBYuXChYWVlJGrvvv/9+kcVIxmFqY1efScERI0YYLE4pOOeW9EapVOL999/H77//LiqXy+WoUqUK6tatC0dHR9FrUVFR6NSpE86fP2+wuPbs2YO///4bcXFxBuuDii9TG7cZGRm4ePGixtesra1RpUoVBAcHo1atWrC0tBS9np6ejilTpmDs2LF6j4tMj6mN3fw4OTnBz88PjRo1QmBgIDw8PNTuiYyMRN++ffHbb78VaWxU9IrT2M3t0qVL+P77743WPxlfcR27VLqZ+rjNyMhA//79MW3aNKSlpYlec3R0RM2aNdGwYUP4+fnBxsbG4PGQ6TD1sVtYXbt2NXYIWYydlaSSY/HixWrZ71GjRgnPnz/PuUehUAg7d+4UKlWqJLrPy8tLePv2rUHi6tGjR57ZeVtbW/6lv5QztXGbkJAg6qNKlSrC7NmzhbNnzwrp6emie5OTk4VNmzZp/IvVf/7zH73GRabH1MauIPxvpmBAQIAwZcoUYe/evcKrV6803vvw4UNhxowZasvjLS0thdDQUL3HRqbDFMduQdLS0oSAgAD+/FDKmerYVZ0pePToUUkfL168MEhcZBpMddxmGzx4sKhPc3NzYcyYMcKlS5fUVr8oFAohNDRU+O6774SmTZsK/fv3N2hsZFymOHbPnDkj+Xvs0aNHhZEjR4ri8/DwEDIyMvQeny6YFCS9iI6OFuzt7UUDfdGiRXne/+zZM7X9pmbOnGmQ2LKTguXKlRO6desmzJs3Tzh06JAQExMjzJo1iz/Ul2KmOG6zk4LNmjUTDh8+rNVS4Ddv3gjBwcGiuJycnLhHWwlmimNXEAQhMTFRuH//vqQ6165dE5ydnUWx9evXT++xkWkw1bFbkNw/L1SoUEH4/PPP+fNDKWPKY1c1KUiUzZTHrSAIwqZNm0R9eXp6Cjdu3NC6/ps3bwwWGxmXqY9dqZo0aSKKbeLEicYOKQf/1SC9+OKLL0SD/J133ikwmXHs2DFRHXt7eyE6OlrvsV29elV48uSJxteYFCzdTHHcpqWlCfv27ZNc7/nz52ozV9asWaO3uMi0mOLYLYxVq1aJYrO1tRVSUlKMHRYZQHEcu7dv3xYsLS1z+t+1axd/fiiFTHnsMilIeTHlcRsVFSW4ubnl9OPo6Cj5D4tUcpny2JUqLCxMFBcASclvQ+OeglRoSqUS69evF5XNnj0bMpks33pt2rRBixYtcq4TEhKwdetWvcdXv359VKxYUe/tUvFmquPW0tISXbp0kVzP09MTQ4YMEZUdPnxYX2GRCTHVsVsYH3zwAczM/vcjSVJSEp48eWLEiMgQiuPYVSqVGDZsGNLT0wEAvXr1Qs+ePYukbzIdxXHsEpn6uF2wYAGio6NzrhcuXAhfX1+990PFj6mPXalU98uuV68e6tSpY5xgNGBSkArt3LlziIqKyrmuWrUqWrVqpVXdYcOGia53796tx8iI8lYSx23ufwQBMKlSQpXEsevg4AB3d3dRWe5fFKhkKI5j97vvvss5/MnBwQE//vhjkfRLpqU4jl0iUx63aWlp2LhxY851uXLlMHLkSL32QcWXKY9dqZRKJTZt2iQqGzp0qHGCyQOTglRo+/fvF123a9euwCx+7ntzO3nyJJKSkvQWG1FeSuK4dXZ2Fl3zxO2SqSSOXQBITU0VXTs5ORknEDKY4jZ2Hz58iBkzZuRcL1q0CJ6engbtk0xTcRu7RIBpj9tdu3bhzZs3Odf9+/eHXC7XW/tUvJny2JXq77//xrNnz3KuLSwsMGDAAKPFowmTglRo169fF103bdpU67qenp7w9vbOuU5PT0dISIieIiPKW0kct8+fPxddu7q6GikSMqSSOHbDwsJESWw7OztUr17diBGRIRS3sTtixAgkJycDAJo0aYLRo0cbtD8yXcVt7BIBpj1uVZM+rVu31lvbVPyZ8tiVasOGDaLrrl27ws3NzUjRaMakIBVaaGio6LpWrVqS6qver9oekSGUxHH7zz//iK6ZVCmZSuLYnT9/vuh64MCBMDc3N1I0ZCjFaeyuXbsWx48fB5D1V/1ffvlF61kKVPIUp7GbLS4uDjdv3sTp06fx77//IiIiAgqFwuD9kukw5XF7+fJl0XVgYCAAQKFQ4ODBg+jfvz9q1KgBW1tbODk5oVq1aujXrx/Wr1+f88caKrlMeexKER8fj127donKTG3pMADwJ24qlJSUFLV9y6Qe6qF6f1hYWKHjIspPSRy38fHx2L59u6isc+fORoqGDKWkjd3U1FRMnToVmzdvzilzd3fH3LlzjRYTGUZxGrsvX77ElClTcq6/+OIL+Pv7G6QvMn3Faexmq1evHm7evAmlUikqt7OzQ7NmzdCnTx98+OGHsLKyMmgcZDymPG7j4uJw7969nGu5XI7KlSvj4cOHGDRoEM6fP6+xzoMHD7Bt2zZMnz4dixcvxuDBg/USD5kWUx67Um3dulWUxC5btqxJ/n7GpCAVSnR0NARByLm2sLCAh4eHpDYqVKgguo6MjNRLbER5KYnjdv78+UhMTMy5dnNzQ9euXY0YERlCcRy7Fy9eREJCQs51amoqIiMjceXKFezYsUPUf7ly5XDgwAHJ74lMX3Eau59++inevn0LAKhWrRqmT59ukH6oeChOYzeb6tK7bImJiTh8+DAOHz6MmTNn4ocffkDfvn0NGgsZhymP24cPH4pis7e3R0hICJo2barVftgvXrzAhx9+iDt37mDx4sV6iYlMhymPXalUlw6b6koY04uIipXcSQgAsLGxkby8xtbWNt82ifStpI3bc+fOYfny5aKy6dOnw8bGxkgRkaEUx7E7cuRI3LhxI997rK2tMXToUMydO1ftFGIqGYrL2N26davopMLVq1fD2tpa7/1Q8VFcxq5Ur169Qr9+/TB58mR8++23xg6H9MyUx232H12yyWQydO3aNSchaGNjgwEDBuCdd96Bq6srYmJicOrUKfzxxx9ISUnJqbdkyRJUqFAB48aN00tcZBpMeexKER4ejjNnzojKTHHpMMCkIBWS6heYLj84lylTJt82ifStJI3byMhI9O/fX7RPUHBwMMaOHWuUeMiwStLYzWZpaYnx48fjk08+YUKwBCsOYzcmJkb0y+VHH33Eze+pWIxdICuudu3aoVOnTqhbty58fX3h5OSEtLQ0REZG4vz589iyZQsOHDggmoWzdOlSuLq6YurUqXqPiYzHlMetalIwNjYWsbGxAICgoCDs3LkTlSpVEt0zePBgTJ8+HT169MDNmzdzyqdMmYIOHTpwH+0SxJTHrhS//fab6Lp+/fqoXbt2kcehDR40QoWSmpoqura0tJTchup+Jrn/AkRkCCVl3KalpaFXr154+vRpTpm9vT3++OMPyOXyIo+HDK+kjN3c0tPT8c0336BGjRoYPny4aKkxlRzFYex+9tlnOUuMPDw8sHTpUr22T8VTcRi7n3/+OZ49e4a9e/di9OjRaNKkCdzd3WFhYQE7OztUrVoVAwcOxL59+3D69Gm1pXXTpk0rcEY3FS+mPG7zStB4eXnh6NGjagnBbN7e3vj7779Rrly5nLK0tDR+ry5hTHnsaksQBGzatElUZqqzBAEmBamQVDP36enpkttIS0vLt00ifSsJ41apVGLQoEE4d+5cTplcLsfvv/8OX1/fIo2Fik5xHLvXr1+HIAg5H/Hx8bh37x42b96MTp065dynUCiwbt06NG/eHDExMQaNiYqeqY/dgwcPig68WbFiBVxcXPTWPhVfpj52AaB79+5wdXXV6t7mzZvj5MmTcHNzyykTBIF7Z5Ywpjxu82rn22+/hbOzc7513dzc1PYR3LRpk9H/wEn6Y8pjV1snTpxAREREzrWlpSUGDBhQpDFIwaQgFYqdnZ3oWjWzrw3Vb+KqbRLpW0kYt59++qnotGGZTIZffvkF3bp1K9I4qGiVhLFrb2+PatWqYeDAgThw4ACOHDki+iXg5s2bGDJkSJHGRIZnymM3ISEBo0aNyrnu2LGjSf/wTkXLlMeurnx9fdX2ETxw4ADevHljpIhI30x53Gpqx8XFBX369NGq/vvvvw9HR8ec69TUVFy6dEkvsZHxmfLY1ZbqASNdu3bV+g83xsCkIBWK6hdYcnKyaJ8SbSQlJeXbJpG+Ffdx+9VXX2H16tWismXLluGjjz4qshjIOIr72NWkXbt22L9/P8zM/vcjyf79+3H06FEjRkX6Zspjd+rUqXjy5AmArA3Nf/75Z720SyWDKY/dwvjwww9F+7gqlUocO3bMiBGRPpnyuNXUTpMmTWBhYaFVfWtrazRs2FBUduXKFb3ERsZnymNXG4mJidixY4eozJSXDgNMClIhubm5iU4DysjIkHzk9/Pnz0XXUo8cJ5KqOI/bxYsXqy2bmDlzJiZOnFgk/ZNxFeexm58mTZpg0KBBojLVDZqpeDPVsfvo0SNREnDOnDnw9vYudLtUcpjq2C0sMzMztGrVSlQWFhZmnGBI70x53JYtW1atTOpBITVq1BBdS31vZLpMeexqY9u2baKkZNmyZUXb5ZgiJgWpUMqUKaO2GWz2X9u1pXp/zZo1Cx0XUX6K67hduXIlvvrqK1HZhAkTMGfOHIP3TaahuI5dbfTu3Vt0nXu/TCr+THXsxsXFiWYgTJkyBTKZrMAP1e+7GzZsEL3u5ORU6NjINJjq2NWHihUriq6joqKMFAnpmymPWx8fH7XDIxwcHCS1oXp/9unFVPyZ8tjVhurS4YEDB8Lc3LzI+tcFk4JUaKpfZCEhIZLqh4aG5tsekSEUt3G7ceNGjBs3TlT28ccfY8WKFQbtl0xPcRu72vLx8RFdv3r1ykiRkKGU1LFLJV9JHbuqyzUzMjKMFAkZgqmOW7lcrjYzUPVgiIKo7jNnY2NT6LjIdJjq2C3Io0ePcPr0aVFZcdjeiUlBKrS6deuKrqXM7nj58iUeP36cc21hYYFatWrpKTKivBWncbtjxw58/PHHotks/fr1wy+//CKaXk+lQ3Eau4Wh7d5CVHyUlrFLJU9JHbuqf3zJvccgFX+mPG7r168vun79+rWk+qrLSU35EAeSzpTHbn42bNgg+n0tKCgIAQEBRdJ3YTApSIXWtWtX0fWxY8e03gz0yJEjouvWrVubxObLVPIVl3F78OBBDBgwAAqFIqesS5cu2Lx5s+hgBio9isvYlSoiIkJ0rWnPISreTHHs+vr64ujRo5I/Bg8eLGqnffv2otf37NlT6NjIdJji2NWHM2fOiK5VlxNT8WbK47Z79+6i66tXr0qqr3q/6h6DVLyZ8tjNiyAI2Lhxo6jM1A8YyWbai5upWGjatCnc3NwQHR0NAHj48CFOnjyJ1q1bF1h33bp1ousePXoYJEYiVcVh3J46dQp9+vRBenp6Tlnr1q2xfft2zqIqxYrD2NXFX3/9JbquU6eOkSIhQzHFsWtnZ4e2bdtKrqeaTClfvrxO7VDxYIpjt7BOnTqF8PBwUVmbNm2MFA0ZgimP244dO8La2jpnGfDNmzdx//59VKtWrcC6d+7cUVseqnpoDhVvpjx283L69Gk8evQo59rS0hIDBgwokr4Li9NMqNDMzMzUsuBz5swpMJv/999/459//sm5tre3R79+/QwRIpEaUx+3V65cQbdu3ZCSkpJT1rhxY+zduxfW1tZ674+KD1Mfu7oIDQ3F+vXrRWWm8osz6U9JHLtUOpS0sZuUlITx48eLymrXro2qVasaKSIyBFMet7a2thg0aJCobP78+VrVnTt3rui6ZcuWJnGiN+mPKY/dvKgeMNKtWze4uLgUSd+FJhDpQVRUlGBnZycAyPlYtGhRnvc/e/ZM8Pb2Ft0/ffr0AvvJfT8A4cSJE4WKe9asWaL2hgwZUqj2qHgx1XF7+/ZtwdXVVVSnbt26QmxsrMR3SCWVKY7d+Ph4YfTo0cLTp08lvZdbt24JFStWFPVTuXJlITk5WVI7VDyY4tjVBX9+KH1MdeyOHz9eeP78uaT38e6776r1s3PnTq3boOLDVMetIAjC06dPBWtra1G9devW5Vtn5cqVan0dOnSowL6o+DHlsasqKSlJsLe3F7Xz119/SW7HWJgUJL1ZuHCh2hfV6NGjRT+oKBQKYdeuXUKlSpVE93l6emqV8NDlizYlJUU4evSoxo/BgweL2mvfvn2e97548aIQT4dMlamN2xcvXgienp6i+21tbYU//vgjz7GZ3weVXKY2dmNjYwUAgoWFhdC1a1dhw4YNwoMHDwSlUql2b1pamnD27Flh1KhRgoWFhagPmUwm7N27V5dHQsWEqY1dXTApWDqZ4tgFIFhZWQk9e/YUNm/eLDx69EjjfU+ePBG++eYboVy5cmp99OzZU8JToOLGFMdtNtXvpTKZTBgzZozw5MkT0X0RERHCqFGjBJlMJrr/gw8+kPIoqJgx5bGb24YNG0RtlCtXTsjIyJDcjrEwKUh6o1AohK5du6p9YcnlcqFq1apCvXr1BCcnJ7XXy5QpI5w5c0arPnT5on306JFaPV0+1q9fX7gHRCbJ1MbtiRMn9DJesz+o5DK1sZudFFT9sLe3F6pVqyYEBwcLDRo0EKpVq6aWCMz9y8DatWv19ITIVJna2NUFk4KlkymOXU3fSx0cHIQaNWoIDRs2FOrVq6f2x8bcHy1atODM7BLOFMdttszMTI2xyWQyoWrVqkJwcLBQtWpVjWO3fv36QkJCQiGeDJk6Ux67uanOvp40aZLkNoyJvzGSXqWkpAj9+/fXOmHh6uoq6QtPly9aJgWpIKY0bpkUJClMaezmlRTU9qNatWrC8ePHC/9QqFgwpbGrCyYFSy9TG7u6fs81MzMTvvjiCyE9Pb1wD4SKBVMbt7mlpqYKQ4YMkTR+u3fvzoRgKWHKY1cQsmaxqs5gvXXrlrQ3aWQ8aIT0ytraGlu2bMH27dtRt27dPO+ztbXFp59+ipCQEJ4WRUbHcUvFlSmNXUdHR5w6dQpffvklGjZsCEtLywLrWFhYoE2bNti8eTNu3bql1alyVDKY0tglksLUxu6aNWvQv39/VKxYUav7y5UrhwkTJiAsLAxLliyBhYWFwWIj02Fq4zY3Kysr/Pbbbzh48CCaNWuW530ymQyNGjXCX3/9hT179sDOzq5I4iPjMuWxCwAbN24UHYASFBSEgICAIutfH2RC7ndApGcPHjzAxYsX8fz5c6Snp8PJyQl+fn5o1qwZT1Alk8VxS8WVKY3dtLQ0hISEIDw8HC9fvkRCQgKArOShk5MTatasidq1a2uVPKSSz5TGLpEUpjR2Y2JiEBoaioiICERFRSEpKQlyuRzOzs5wc3NDvXr1eMIwATCtcavq+fPnOH/+PCIiIpCamgpnZ2eUL18ezZo14ynDZNJjt7hiUpCIiIiIiIiIiKiU4fJhIiIiIiIiIiKiUoZJQSIiIiIiIiIiolKGSUEiIiIiIiIiIqJShklBIiIiIiIiIiKiUoZJQSIiIiIiIiIiolKGSUEiIiIiIiIiIqJShklBIiIiIiIiIiKiUoZJQSIiIiIiIiIiolKGSUEiIiIiIiIiIqJShklBIiIiIiIiIiKiUoZJQSIiIiIiIiIiolKGSUEiIiIiIiIiIqJShklBIiIiIiIiIiKiUoZJQSIiIj179OgR9u/fj1WrVuGbb77BggUL8OOPP2Lz5s04deoUEhISjB2iSUtOTsaqVavQs2dPeHt7w97eHjKZTPSR29ChQ0Wv/fbbbwaN7+TJk6L+WrVqZdD+iFTNnj1bNAZnz55t7JBKlZL+/L29vUXv7/Hjxwbtr6Q/TyIiU2Zu7ACIiIhKgn/++QebNm3CX3/9hVevXuV7r5mZGWrWrInu3btj8ODBqFWrVhFFafpOnTqF999/H69fvzZ2KET58vb2RkRERJH0NWTIEIMnu4mIiKj04UxBIiKiQrh06RKaNm2Kd955B7/88kuBCUEAUCqVCAkJweLFi+Hv74/mzZvjzJkzRRCtabt9+zY6derEhCARERERURHgTEEiIiIdKBQKzJo1CwsXLoQgCHneZ2ZmBmdnZ6SlpSExMVHjPWfPnkWLFi3wxRdfYMmSJYYK2eRNmDABKSkpOdc2NjZ47733UKdOHdja2hoxMiIiIiKikodJQSIiIokyMjLwwQcfYMeOHWqvVa5cGX369EGnTp0QGBgIV1dXmJllTcxPTExEaGgoTp48iW3btuHy5cuiumFhYUUSvyl6+PAhjh8/nnNdpkwZXLx4EQEBAUaMiihvCxYs0Hp/0PPnz2Pjxo2isp9//lnrvmrUqCEpNiIiIiJtMClIREQk0UcffaSWEHRycsKMGTMwduxYWFpaaqxnZ2eH4OBgBAcHY8qUKbh48SKmT5+OY8eOFUXYJu3s2bOi6z59+midEPztt9+43xoVuYEDB2p9r7W1tVpScNSoUfoOiYiIiEgS7ilIREQkwQ8//IDff/9dVObl5YVz587h888/zzMhqEmjRo1w9OhRbNq0Cfb29voOtVi5e/eu6LpevXpGioSIiIiIqHRgUpCIiEhLjx8/xldffSUqc3V1xZkzZ+Dn56dzu4MGDcKlS5dQtWrVwoZYbL19+1Z07eTkZJQ4iIiIiIhKCyYFiYiItDR79mwkJyeLyv7zn/+gcuXKhW67Zs2aWLp0aaHbKa5Un2v2PoxERERERGQY3FOQiIhIC69evVJbNty6dWt88MEHeutDl0TYmzdvcP78ebx69QpRUVGwtraGu7s7fH190aBBA8jlcr3Fl9vjx49x4cIFPH36FJmZmXBzc4Ovry+aNWsmaQl1tvxOcC4qd+/exfXr1/H8+XNkZGTA3d0dgYGBCAoKgkwmM0ifaWlpOc8xKioK6enpcHd3h5eXF5o3bw4bGxu99ykIAq5fv45r167h9evXMDc3h7u7O+rWrYvAwEC9vtfIyEhcunQJkZGRiI6OhlKphIODA6pUqYLatWvDy8urUO0b4/kVF69evcK5c+fw6NEjpKWlwcXFBd7e3mjRooVBTvN++/Ytzp8/j/DwcMTFxcHCwgK+vr7o3bt3gXWzx+S9e/cQFRWF+Ph4uLi4oFy5cmjatCk8PDz0Et/169dx//59xMXFITU1FWXKlIGDgwMqVaoEX19f+Pj4FLqfbEXx/AVBwLVr1xAWFoaoqCgkJSXBzc0NHh4eaNKkiV6em66USiUuXLiA+/fv4+XLl5DL5fDy8kJwcDB8fX2NFhcREakQiIiIqEBLly4VAIg+tm3bZrR4tm3bJjRp0kQwMzNTiyv7w8XFRfjoo4+ER48eSWp7yJAhonbWr1+f89qRI0eEJk2a5Nmnra2t8Pnnnwtv3rzJt49Zs2bl2UZ+H5UrV5YUrza2bNki1K5dO88+K1SoICxbtkzIyMgQBEEQTpw4IXq9ZcuWkvoTBEE4deqU0LVrV8HGxibPfq2srISuXbsKV65ckdR25cqVRe1kf/4VCoWwcuVKwdvbO9/3unLlypz3qovExERhyZIlQp06dQSZTJbv59PX11eYOHGicOfOHUl9GPL5GcL69evV4isM1a+fWbNm5bx26dIloUOHDnk+e0tLS+Gjjz4Snj17pnP8Q4YMyXnt8uXLQteuXQW5XK7V12tu4eHhwvDhwwUPD488P48ymUwIDg7W+fvtnj17hLZt2+b7vTL398yePXsKmzdvFhQKRZ5tFvXzV/XixQvh008/LfC5BQUFCb/99lu+70WTvL6HaCM1NVWYM2eO4OnpmWds9evXF/bs2ZNTJ7/nSUREhsWkIBERkRZatmwp+qXF1dVVSE9PL/I4nj59KjRu3FhSIs3S0lKYN2+e1n1oSrJlZmYK48eP17pPHx8fITw8PM8+TCEpmJSUJHTr1k3rvhs3bixERUUVKikYGRkpdO7cWdJ7lslkwpgxY4TMzEyt+tD0C310dLTwzjvvaN1n586dheTkZK3fV7aNGzcKbm5uOn1uTeX5GUJRJQUXL16sMTmn6cPNzU24fPmyTvFnJwXnzp2bb7Itr6RgRkaGMHnyZMHCwkLS57JFixZCVFSUVjEnJSUJPXv21GksAhBiY2NN5vnn9sMPP+SbDNf0UadOHeHevXta96FrUvDevXtCzZo1tY5r5MiRQmZmJpOCRERGxA17iIiICpCRkYELFy6Iypo2bQoLC4sijSM0NBRNmzZViyWbg4ODxqW76enpmDFjBoYNGwalUqlT35988gl++OEHUZmlpSWcnZ01LjcNDw9Hx44dkZKSolN/hpacnIyuXbvir7/+0vi6nZ0drK2tRWUXLlxA586dkZqaqlOfYWFhaNy4MQ4cOKDxdVtbW40HrAiCgJUrV6Jnz57IzMyU3G98fDzatm2L06dPi8ptbGzg4OCgsc6BAwcwYsQIrfsQBAGTJk3Chx9+iOjoaI33lClTBs7OzjrvF2ms51dczJ07F1OnToVCocgpMzc3h4uLi8ZtBKKjo9GxY0e8fv1ap/7mzJmDmTNnir6nyGQyODs757ttQUJCArp164alS5ciIyND7XUrK6s8Y/7nn3/QpEkTPHv2rMD4evfujd27d2t8zdraGm5ubrC3t9fbcvmieP6TJ0/G+PHj1fZgBQALC4s8D2i6efMmmjVrhsuXL2vdl1QPHjxA69at1U6Sz+bk5ARzc/HOVatXr8Znn31msJiIiEgLRk5KEhERmbzr16+rzXCYM2dOkcaQmJgoVKtWTS2ORo0aCdu3bxcSEhIEQRAEpVIphIeHCwsXLhQcHBzU7l+wYEGBfanOvMu9XLhChQrC999/Lzx8+DDn/tTUVOHgwYNCcHCwWn/Tp0/X2Mfly5eFn3/+OedDdfbjhx9+KHo9+2Pz5s0FxqvNTMFRo0apxerr6yv89ttvQkxMTM59z549E7777jvB3d1d9Mxz19NmpmB0dLRQsWJFUT1zc3Nh0KBBwpEjR4T4+Pice1NSUoSjR48KPXr0UIvxyy+/LLAv1Vk+uT9/wcHBwn//+1/Re3zz5o2wbt06oXz58mr9HTt2rMD+BEHzzE+5XC4MHTpUOHDggOj9KZVK4f79+8Lvv/8u9OvXT7C1tRUK+pG0KJ+fIRh6pmDjxo1zlqs6OzsL8+fPF0JCQgSlUikIgiBkZmYKp0+fFtq3b68Wx6BBgyTH7+fnlzND0MrKSpg4caJw6dKlnNmYmZmZwt27d4UffvhB1I5SqRS6dOmiFkPLli2FLVu2CC9evMi5V6FQCFeuXBEmTJggWFlZie5v1qxZvjM///jjD7U+WrVqJWzbtk149eqV6N7MzEwhLCxM2LZtmzB8+HChbNmyAiBtpqChn78gCMLq1avV6lpbWwvTpk0T9ZWSkiLs379faNu2rdr9np6eQnR0dIF9SZ0pmJ6eLtSpU0etv7Zt2wr79+8XUlJSBEHI+pzeunVLmDRpkmiWqOr3VM4UJCIqOkwKEhERFWDHjh1qv+zs2rWrSGMYOXKkWgxTpkzJd6+oJ0+eqCUSzc3NhX///TffvlSTbNkfnTt3zkk+apKWlqb2S6+Hh4dWy6wLsy+g1LqnTp1S2++re/fu+S6XjYqKEurXr6/xuWiTFFRNhFSuXFmrpYMbN24UzM3Nc+rJZDLh4sWL+dZR/YU++2PmzJn51nvy5Ing5eUlqtOzZ88CYzx8+LDa86xatapw69atAusKQlZSsqDl7UX5/AzB0EnB7I/g4GC1pFduSqVSGDp0qKiOpaWlEBkZKTn+7CSTtp9nQRCEb775Ri2ptWnTpgLrXb16VS1p/e233+Z5f8eOHUX3jhs3TusY09PThS1btuT7/aCon/+DBw/UlgxXqFBBuHv3br71Fi9erBZj7969838AgvSk4Ny5c9X6KegPUFeuXBGcnZ01PkcmBYmIig6TgkRERAX4z3/+o/ZLy6lTp4qs/2fPnokSG4D2s0siIiLUZgy+9957+dbRlBSsV6+ekJqaqlWsqrN6jh49WmC9okwKtmvXTnR/7dq1c2ay5CcyMlLjxv4FJQWPHj0qut/V1VV48OCB1u9v2bJlovp9+vTJ935NScFPP/1Uq762bdsmqmdubl7gswkMDFRLVuSXGJGqqJ+fIRRFUrBixYqiGaB5SUxMzJkNl/3xyy+/SI7f3NxcuHbtmtYxv3nzRrCzsxO1IeWPKxcuXBB9H/T09BTS0tI03pv769TCwkI0k1Qfivr5jx49WnS/lZWVcPv2ba1i/eyzz9RiLaiulKRgUlKS4OTkJLp/xIgRWsV28uRJjQeyMClIRFR0uKcgERFRARITE9XK8tq7yRBWrVol2gvNyckJ3333nVZ1K1WqhLlz54rKdu3ahadPn0qKYeXKlbCysirwvgoVKqBLly6isqtXr0rqy5DCw8Nx7NgxUdkPP/ygtn+gJu7u7li4cKHkPr/55hvR9YIFC+Dj46N1/fHjx6Nq1ao517t27UJUVJTW9V1cXNRiyEuvXr3g4eGRc52ZmYkbN27kef/BgwfVXl+/fj3Kli2rdXwFMfbzKy6WLFkCFxeXAu+ztbXFwIEDRWW6fI2OGjUKdevW1fr+n3/+WfS9tH///ujZs6fW9Rs1aiSK+8WLF9i3b5/Ge2NjY3P+P3vvQEMz1POPj4/Hxo0bRWVTpkyBv7+/VnHNnz8fFSpUEJWp7g9bGH/++Sfevn2bc+3s7IwlS5ZoVbdly5Zqz4KIiIoWk4JEREQFSE9PVyuztbUtsv5VD1YYMGAAXF1dta4/bNgwUbwKhQJHjhzRun5gYCCaNGmi9f3NmjUTXee18bwx7Nu3D4Ig5FzXqlULrVq10rr+wIED4ejoqPX90dHRoiSko6MjhgwZonV9IOuwgr59++ZcK5VKnDlzRuv6gwcP1nq8yuVyNGrUSFSW3+dv+/btouuGDRuiXbt2WsdWEFN4fsWBq6ur6D0WRB9fo5988omk+7ds2SK6Hj9+vOQ++/fvL7o+deqUxvty/9Hm9evXkv8IIpUhn/+pU6eQlJSUcy2XyzFmzBit+7K1tcXw4cNFZXkd1qOLvXv3iq4/+OADODs7a11fynshIiL9Y1KQiIioAJpO9M39S5ohJSUl4ebNm6KyPn36SGrDzs4OHTt2FJWdO3dO6/otW7aU1F/uWVkARLNIjO3ixYui6x49ekiqb21trfYs83P69GlRErJVq1ZazUpUVb9+fdH1+fPnta5ryM/fyZMnRdeDBg2S1FdBTOH5FQfNmjVTO9k1P4X9GnV1dUXt2rW1vj8mJgZ37tzJuXZ0dJT0h4Zs2n4eGzZsmPP/SqUSffv2xaNHjyT3py1DPn/V79VNmzZFuXLlJMX33nvvia6fPXumt0RpYb+nNm7cWPL7ISIi/dH+Xy8iIqJSys7OTq0sLi6uSPoOCQkRLR2WyWQICgqS3E6DBg2wY8eOnGvVRGN+vL29JfWlulQvPj5eUn1DUl3qqppk0Eb9+vXx559/anXvhQsXRNdJSUlYtWqV5D5DQ0NF1y9fvtS6rqE+f3FxcXj48KGorGnTppL6KogpPL/ioKi/RqUkBIGsxFHu5K6jo6NOn0eFQiG6zuvzOGrUKOzfv1/Uf/Xq1dG5c2f07NkT7777LipXriy5/7wY8vmrfq9u0KCBpL4AwM/PDzY2NkhOTha1W7FiRclt5RYVFaX2OahXr57kdurVq4eDBw8WKhYiItINk4JEREQFKF++vFrZmzdviqRv1X6cnZ0lLV/NVqVKlXzbzY/U/RPlcrnoWvUXeWOKiYkRXeuSGJCSAHj9+rXo+tixY2p7GurCFD5/mvblk7LXnzZM4fkVB0X9NSpl+wJA/fP45MkTjB49WlIbmuT1eezatSs++eQTrFmzJqcsMzMTe/fuzVnu6uXlhSZNmuCdd97Bu+++i1q1aukchyGfv+p7VP1erm1/lSpVEi1T1sfXgOr3UxsbG7i7u0tuR2pSlYiI9IfLh4mIiAqgKdEhZaZdYeTeMB8AHBwcdGpHNZEo5RdCmUymU5+mSHWZni7PU0pS1lDJp9wzfgpiqM+fakJAJpPpPD7zYgrPrzgo6q9RTbOn82OMz+Pq1auxfPnyPL9enz17hm3btmHcuHHw9/dHQEAAfvjhB6SmpkqOw5DP3xT+DciLPr6fAtK+pxIRkX4xKUhERFQAf39/tX0Fr1y5YqRoqDjRdEiNPuReilmS8fmVDIb6PBZk4sSJePz4MX788Ue0bNky3xPU79y5gwkTJqBmzZolbs9JIiKivDApSEREVAALCws0btxYVHbu3DlkZGQYvG/VUxx13Z9PdQ9EFxcXnWMqzlSX+enyPKXsJ6n6nL/44gsIglDoD9UDPoxBdQmpIAh63z+yJD+/0kT189iwYUO9fB61Se46OTlhzJgxOHnyJN6+fYuTJ09i/vz56Nixo8YZjxEREWjXrh2uX7+ur7dfKKb8b4A+vp8CRbdHLxERqWNSkIiISAvdunUTXUdHR+fsTWVIqomX2NhYnX6BUj15s7QmBVWfZ0REhOQ2Hj9+rPW9qvtrqS65Lc407R324MEDg/ZRkp5faWIqn0dra2u0bNkSX3/9NQ4ePIiYmBgcOHAAnTt3Ft2XlJSEsWPHGiVGVarfs6R8/8mmUCjw5MkTUZk+/g1QjS05ORnR0dGS29HlPRERkX4wKUhERKSFQYMGwdxcfD7XTz/9ZPB+/fz8RP0KgoB///1Xcjuqy53r1KlT6NiKo8DAQNG1Ls9SSp26deuKrq9duya5P1Pl6Oiott/muXPn9NpHSX5+pYnq5/Hx48cmMTvM0tISnTp1wv79+/HNN9+IXjt79qxOfzTQN9WTnnXZuiI0NFRt/0V9/Bvg7u6udhCXLt9T+XVNRGQ8TAoSERFpoVy5chgwYICo7Pjx49iyZYve+lAqlWpltra2ar+87dq1S1K7SUlJOHz4sKisadOm0gMsARo1aiS63rNnj6T6qampas8yP+3atRNdX79+HS9evJDUpylr1aqV6Pr333/Xa/sl/fmVFlWrVkXVqlVzrhUKBQ4ePGjEiNRNnjxZLcFVVAdK5Uf1e/W5c+cQGRkpqY0dO3aIrr28vFCxYsVCxwYU/nvqhQsX8OrVK73EQkRE0jEpSEREpKU5c+agTJkyorJx48bpZTZJWFgYJk+erPG1Ll26iK5///13tRMp8/Prr78iMTEx51oul6NDhw66BVrMde3aVXRSaEhICE6dOqV1/d9//13txM38VKxYEQ0bNsy5ViqVWLJkidb1TV2/fv1E15cuXcLRo0f11n5Jf36lyXvvvSe6XrJkiUkd+CKTyVC5cmVRWVJSkpGi+Z+WLVvC1tY25zozMxM///yz1vWTk5Oxdu1aUZnqvymFobq1xpYtWyT9+7Ry5Uq9xUJERNIxKUhERKQlb29vLFq0SFQWExOD5s2b4+7duzq3+/vvvyM4OBgPHz7U+PqoUaNgYWGRc/3mzZs8E4iqnj17hpkzZ4rKevfuDS8vL53jLc58fHzQpk0bUdm4ceOQlpZWYN3o6GhMmzZNcp+qz3/lypXYv3+/5HaymVIipX379qhXr56o7KOPPsLr16/11kdJfn6lyaRJk0TJrevXr+Orr77Sez8KhUKnehkZGWp7YpYrV04fIRWKg4MDhgwZIipbsmQJ7t27p1X9mTNn4tmzZ6Ky8ePH6y2+/v37w9HRMec6NjYWX375pVZ1T506pffZxUREJA2TgkRERBJMmDBBbRnxs2fP0KRJE6xYsQLp6elat3Xp0iW0a9cOgwYNQkJCQp73eXp64uOPPxaV/frrr5g5c2a+CY7nz5+jXbt2oplt5ubmBvlFvDj5+uuvRde3bt1Cv379kJKSkmed6OhodOjQQfKyPSBrVk779u1zrhUKBd577z2sWrVKUjtRUVFYsGABOnbsKDkGQ/rmm29gZva/HymfP3+OZs2a4c6dO1rVj42Nxfz58/N8vaQ/v9LCw8NDLam+ZMkSjB49Ot+vPVWpqanYsGED6tevr/FQi1u3bqFu3brYsGGDpHZnzJghas/W1hbBwcFa1zekSZMmwcbGJuc6JSUF7du3R3h4eL71li1bhmXLlonK+vTpg1q1auktNhsbG0ycOFFU9ssvv6j9AU3Vv//+i169ejFJT0RkZEwKEhERSbR+/Xr07t1bVPb27Vt8/vnnqF69OiZPnoy///4b0dHRon0Ck5KScPnyZSxduhSNGjVCo0aNcOzYMa36XLZsGapVqyYqmzdvHlq0aIHdu3eLNpF/9OgRFi9eDH9/f7UZjHPnzlWb2VXatGrVCiNGjBCV7d27F4GBgdi4caNo6duLFy/www8/oFatWjkb6Ddu3Fhyn1u2bIGvr2/OdWpqKkaPHo3atWvjxx9/xO3bt9VmOEVFReH48eP49ttv0bJlS5QvXx7Tp0/H8+fPJfdvSG3btsWMGTNEZeHh4QgMDMTHH3+Mw4cPi5avC4KA8PBwbNmyBf3790fFihXV6qsqyc+vNPnqq6/Qp08fUdmqVavg7e2NmTNn4ty5c2qJvMTERFy6dAlr1qxBnz594ObmhqFDh+Z7OMWNGzcwdOhQuLu74/3338e6detw7do1pKamiu6Ljo7Grl270LZtW7Vl6cOHDxfNbDSmqlWrYsWKFaKyiIgI1KlTB7NmzcK9e/dykmupqak4dOgQOnTooDaj3NPTE6tXr9Z7fF999RX8/f1FZdOmTUO7du1w6NChnJnYgiDgzp07mDJlCho3bpzzvVZ1X0IiIio65gXfQkRERLlZWlpi69atmDFjBhYvXiya6RARESGanWFmZgZnZ2dkZGQgPj4+zzZlMpnaybi52draYs+ePWjfvr1oKdjZs2dx9uxZAFmnwaampua5FPbjjz/WellXSbdixQqEhYXh9OnTOWX379/PWaZnb2+PzMxMtQRFcHAwZs2ahU6dOknqz8XFBYcPH0bPnj1x69atnPLbt29j3LhxALLGgIODA2QyGRISEnReBmkMM2fORFxcHL777rucMoVCgfXr12P9+vUAsmYUWVlZIS4uTuOhOvkp6c+vtJDJZNi4cSPMzMywbdu2nPLIyEjMmzcP8+bNA5D1/c7a2hrx8fHIyMjQub+kpCRs3boVW7duzSkrU6YMbG1tkZycrHYib7Z69eph4cKFOvdrCJ988gnu3bsnmvmXnJyMuXPnYu7cubCwsICdnV2e+/m5ublh9+7dcHV11XtslpaW2LlzJ1q1aoWXL1/mlB87dgzHjh2DTCaDk5MTEhISkJmZKao7btw4uLi44OLFi3qPi4iICsaZgkRERDqQy+VYuHAhzp07l+/MMaVSiZiYmHwTgm3btsXly5cxZ86cfPv08/PD+fPn8+wvLi5OY0LQ0tISc+fOxbp160TLPEszW1tb7N+/P88N9xMSEtQSgk2aNMGBAwdgbW2tU59Vq1bFhQsXMGzYMMjlcrXXBUFAXFwc3r59m2dCq6DksbGYmZlhxYoVWLt2LZydnTXek5ycjNjYWI0JwdyHv+SlJD+/0sTGxgZbt27F8uXL4eDgoPGepKQkxMTE5JsQrFmzpsavxYLGUkpKCqKjo/NMCPbs2RMnT54ULdc1FUuXLsUPP/ygMbaMjIw8E4J16tTBuXPnDLocunr16jhx4gSqV6+u9pogCIiNjVVLCI4aNUptBiQRERUt/mZARERUCI0bN8b58+dx+vRpDBs2DB4eHgXWMTMzg7+/P6ZPn4779+/j6NGjCAoK0qo/Ly8vnD9/Hlu3bkWTJk3yTfI5Ozvjo48+wt27dwtcnlka2dnZYd++ffj999/Vlr7l5unpiWXLluH06dNwc3MrVJ82NjZYu3YtwsLCMGrUKFSoUKHAOlZWVmjVqhUWLVqEhw8fmvTG/MOGDcOjR48wc+ZMteXumtSsWRNTp05VO+AhLyX9+ZUmEydOREREBObNm5fv11+27ITu5MmTceHCBYSGhsLOzk7tvsDAQISEhOCbb75Bu3bt8kw85mZlZYVevXrh2LFj2LVrl1Z1jGXcuHG4f/8+Pv3003z/vZHJZKhfvz7Wr1+Pa9euafX1WFg1atTAzZs3MWvWLJQvXz7P++rXr4+9e/fi559/1pjgJyKioiMTuLsrERGRXoWHhyMkJARPnz5FfHw8MjMz4ejoCGdnZ1SqVAn169fX+MusLt68eYNz587h1atXiI6OhpWVFdzd3eHr64vg4GD+wiVBaGgorl27hhcvXiAjIwMeHh4IDAxE/fr1DTrD8v79+7h58yZiYmIQExMDMzMz2Nvbw8PDAzVq1ED16tVhZWVlsP4NKSIiAlevXkVUVBRiYmJgbm4OBwcHVK1aFQEBAfD09Cx0HyX5+ZUmkZGRuHz5MiIjIxEdHY2MjAzY2dnBxcUF1apVg5+fn07JOqVSifv37+PBgwc535PT09NhZ2cHZ2dn1KpVCwEBAShTpowB3pVhCYKAf//9F2FhYYiKikJycjJcXV1RtmxZNG7cGGXLljVabEqlEufPn8e9e/fw6tUrmJubo0KFCmjYsKFof1AiIjIuJgWJiIiIiIiIiIhKGS4fJiIiIiIiIiIiKmWYFCQiIiIiIiIiIiplmBQkIiIiIiIiIiIqZZgUJCIiIiIiIiIiKmWYFCQiIiIiIiIiIiplmBQkIiIiIiIiIiIqZZgUJCIiIiIiIiIiKmWYFCQiIiIiIiIiIiplmBQkIiIiIiIiIiIqZZgUJCIiIiIiIiIiKmWYFCQiIiIiIiIiIiplmBQkIiIiIiIiIiIqZZgUJCIiIiIiIiIiKmWYFCQiIiIiIiIiIiplmBQkIiIiIiIiIiIqZZgUJCIiIiIiIiIiKmX+D+Fi2wM27Tp5AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "\n",
    "matplotlib_setup()\n",
    "\n",
    "# Group data by model and confidence, then average the HOTA scores\n",
    "curve_data_model_avg = df.groupby([\"model\", \"conf\"])[\"HOTA\"].mean().reset_index()\n",
    "\n",
    "# Set unique models\n",
    "models = curve_data_model_avg[\"model\"].unique()\n",
    "\n",
    "# Define bold colors for the models\n",
    "colors = sns.color_palette(palette='viridis', n_colors=len(models))\n",
    "color_map = {i: plt.cm.tab10(i) for i in range(len(models))}\n",
    "\n",
    "# Create the plot\n",
    "plt.figure(figsize=(14, 10))\n",
    "\n",
    "for i, model in enumerate(models):\n",
    "    model_data = curve_data_model_avg[curve_data_model_avg[\"model\"] == model]\n",
    "    plt.plot(\n",
    "        model_data[\"conf\"],\n",
    "        model_data[\"HOTA\"],\n",
    "        label=model,\n",
    "        color=color_map[i],\n",
    "        marker='o',\n",
    "        linestyle='--',\n",
    "        linewidth=8,\n",
    "        markersize=12\n",
    "    )\n",
    "\n",
    "# Add plot details\n",
    "plt.title(\"YOLOv8m vs. YOLO11m: Avg. HOTA Scores\", fontsize=32)\n",
    "plt.xlabel(\"Confidence Threshold\", fontsize=32)\n",
    "plt.ylabel(\"HOTA Score\", fontsize=32)\n",
    "plt.xticks(fontsize=30)\n",
    "plt.yticks(fontsize=30)\n",
    "\n",
    "# Add legend\n",
    "plt.legend(title=\"Model\", fontsize=35, title_fontsize=35, loc='lower left')\n",
    "\n",
    "# Save and show the plot\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"average_hota_scores_by_model.png\", dpi=600)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
